NeurIPS 2023 Wednesday 12/13

Timezone: America/Chicago

Full Schedule Sun 12/10 Mon 12/11 Tue 12/12 Wed 12/13 Thu 12/14 Fri 12/15 Sat 12/16

Registration Desk

7:30 AM - 6:00 PM

Invited Talk

Sketching: core tools, learning-augmentation, and adaptive robustness

Jelani Nelson

8:30 AM - 9:20 AM

'Sketches' of data are memory-compressed summarizations that still allow answering useful queries, and as a tool have found use in algorithm design, optimization, machine learning, and more. This talk will give an overview of some core sketching tools and how they work, including recent advances. We also discuss a couple newly active areas of research, such as augmenting sketching algorithms with learned oracles in a way that provides provably enhanced performance guarantees, and designing robust sketches that maintain correctness even in the face of adaptive adversaries.

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Speaker Bio

Jelani Nelson is a Professor of Electrical Engineering and Computer Sciences at UC Berkeley, and also a Research Scientist at Google (part-time). He is interested in randomized algorithms, sketching and streaming algorithms, dimensionality reduction, and differential privacy. He is a recipient of the ACM Eugene L. Lawler Award for Humanitarian Contributions within Computer Science, a Presidential Early Career Award for Scientist and Engineers (PECASE), and a Sloan Research Fellowship. He is also Founder and President of AddisCoder, Inc., a nonprofit that provides algorithms training to high school students in Ethiopia and Jamaica.

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Oral

Oral 3A Neuro

10:00 AM - 10:45 AM

3 Events in this session

Brain Diffusion for Visual Exploration: Cortical Discovery using Large Scale Generative Models

Andrew Luo · Maggie Henderson · Leila Wehbe · Michael Tarr

Cinematic Mindscapes: High-quality Video Reconstruction from Brain Activity

Zijiao Chen · Jiaxin Qing · Juan Helen Zhou

Human-like Few-Shot Learning via Bayesian Reasoning over Natural Language

Kevin Ellis

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Oral

Oral 3B NLP/Tools

10:00 AM - 10:45 AM

3 Events in this session

ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings

Shibo Hao · Tianyang Liu · Zhen Wang · Zhiting Hu

Toolformer: Language Models Can Teach Themselves to Use Tools

Timo Schick · Jane Dwivedi-Yu · Roberto Dessi · Roberta Raileanu · Maria Lomeli · Eric Hambro · Luke Zettlemoyer · Nicola Cancedda · Thomas Scialom

Learning Transformer Programs

Dan Friedman · Alexander Wettig · Danqi Chen

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Oral

Oral 3C Diffusion Models

10:00 AM - 10:45 AM

3 Events in this session

Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation

Diederik Kingma · Ruiqi Gao

Entropic Neural Optimal Transport via Diffusion Processes

Nikita Gushchin · Alexander Kolesov · Alexander Korotin · Dmitry Vetrov · Evgeny Burnaev

DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models

Tsun-Hsuan Johnson Wang · Juntian Zheng · Pingchuan Ma · Yilun Du · Byungchul Kim · Andrew Spielberg · Josh Tenenbaum · Chuang Gan · Daniela Rus

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Poster

Poster Session 3

10:45 AM - 12:45 PM

601 Events in this session

Neural Modulation for Flash Memory: An Unsupervised Learning Framework for Improved Reliability

Jonathan Zedaka · Elisha Halperin · Evgeny Blaichman · Amit Berman

CoDrug: Conformal Drug Property Prediction with Density Estimation under Covariate Shift

Siddhartha Laghuvarapu · Zhen Lin · Jimeng Sun

Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths

Lars Holdijk · Yuanqi Du · Ferry Hooft · Priyank Jaini · Berend Ensing · Max Welling

Towards Symmetry-Aware Generation of Periodic Materials

Youzhi Luo · Chengkai Liu · Shuiwang Ji

Equivariant Neural Operator Learning with Graphon Convolution

Chaoran Cheng · Jian Peng

FABind: Fast and Accurate Protein-Ligand Binding

Qizhi Pei · Kaiyuan Gao · Lijun Wu · Jinhua Zhu · Yingce Xia · Shufang Xie · Tao Qin · Kun He · Tie-Yan Liu · Rui Yan

Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics

Leon Klein · Andrew Foong · Tor Fjelde · Bruno Mlodozeniec · Marc Brockschmidt · Sebastian Nowozin · Frank Noe · Ryota Tomioka

Transfer learning for atomistic simulations using GNNs and kernel mean embeddings

John Falk · Luigi Bonati · Pietro Novelli · Michele Parrinello · Massimiliano Pontil

Learning Fine-grained View-Invariant Representations from Unpaired Ego-Exo Videos via Temporal Alignment

Zihui (Sherry) Xue · Kristen Grauman

OpenShape: Scaling Up 3D Shape Representation Towards Open-World Understanding

Minghua Liu · Ruoxi Shi · Kaiming Kuang · Yinhao Zhu · Xuanlin Li · Shizhong Han · Hong Cai · Fatih Porikli · Hao Su

Transition-constant Normalization for Image Enhancement

Jie Huang · man zhou · Jinghao Zhang · Gang Yang · Mingde Yao · Chongyi Li · Zhiwei Xiong · Feng Zhao

Prototype-based Aleatoric Uncertainty Quantification for Cross-modal Retrieval

Hao Li · Jingkuan Song · Lianli Gao · Xiaosu Zhu · Hengtao Shen

DAW: Exploring the Better Weighting Function for Semi-supervised Semantic Segmentation

Rui Sun · Huayu Mai · Tianzhu Zhang · Feng Wu

PromptIR: Prompting for All-in-One Image Restoration

Vaishnav Potlapalli · Syed Waqas Zamir · Salman Khan · Fahad Shahbaz Khan

Weakly Supervised 3D Open-vocabulary Segmentation

Kunhao Liu · Fangneng Zhan · Jiahui Zhang · MUYU XU · Yingchen Yu · Abdulmotaleb El Saddik · Christian Theobalt · Eric Xing · Shijian Lu

Opening the Vocabulary of Egocentric Actions

Dibyadip Chatterjee · Fadime Sener · Shugao Ma · Angela Yao

Assessor360: Multi-sequence Network for Blind Omnidirectional Image Quality Assessment

Tianhe Wu · Shuwei Shi · Haoming Cai · Mingdeng Cao · Jing Xiao · Yinqiang Zheng · Yujiu Yang

Uncovering Prototypical Knowledge for Weakly Open-Vocabulary Semantic Segmentation

Fei Zhang · Tianfei Zhou · Boyang Li · Hao He · Chaofan Ma · Tianjiao Zhang · Jiangchao Yao · Ya Zhang · Yanfeng Wang

SceneScape: Text-Driven Consistent Scene Generation

Rafail Fridman · Amit Abecasis · Yoni Kasten · Tali Dekel

Unified 3D Segmenter As Prototypical Classifiers

Zheyun Qin · Zheyun Qin · Cheng Han · Qifan Wang · Xiushan Nie · Yilong Yin · Lu Xiankai

Reading Relevant Feature from Global Representation Memory for Visual Object Tracking

Xinyu Zhou · Pinxue Guo · Lingyi Hong · Jinglun Li · Wei Zhang · Weifeng Ge · Wenqiang Zhang

KD-Zero: Evolving Knowledge Distiller for Any Teacher-Student Pairs

Lujun Li · Peijie Dong · Anggeng Li · Zimian Wei · Ya Yang

Learning Mask-aware CLIP Representations for Zero-Shot Segmentation

Siyu Jiao · Yunchao Wei · Yaowei Wang · Yao Zhao · Humphrey Shi

Exploring Question Decomposition for Zero-Shot VQA

Zaid Khan · Vijay Kumar B G · Samuel Schulter · Manmohan Chandraker · Yun Fu

ChatGPT-Powered Hierarchical Comparisons for Image Classification

Zhiyuan Ren · Yiyang Su · Xiaoming Liu

ImageBrush: Learning Visual In-Context Instructions for Exemplar-Based Image Manipulation

ya sheng sun · Yifan Yang · Houwen Peng · Yifei Shen · Yuqing Yang · Han Hu · Lili Qiu · Hideki Koike

DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data

Stephanie Fu · Netanel Tamir · Shobhita Sundaram · Lucy Chai · Richard Zhang · Tali Dekel · Phillip Isola

Exploiting Contextual Objects and Relations for 3D Visual Grounding

Li Yang · chunfeng yuan · Ziqi Zhang · Zhongang Qi · Yan Xu · Wei Liu · Ying Shan · Bing Li · Weiping Yang · Peng Li · Yan Wang · Weiming Hu

Bitstream-Corrupted Video Recovery: A Novel Benchmark Dataset and Method

Tianyi Liu · Kejun Wu · Yi Wang · Wenyang Liu · Kim-Hui Yap · Lap-Pui Chau

Neural-Logic Human-Object Interaction Detection

Liulei Li · Jianan Wei · Wenguan Wang · Yi Yang

Vocabulary-free Image Classification

Alessandro Conti · Enrico Fini · Massimiliano Mancini · Paolo Rota · Yiming Wang · Elisa Ricci

Synthetic-to-Real Pose Estimation with Geometric Reconstruction

Qiuxia Lin · Kerui Gu · Linlin Yang · Angela Yao

Low-shot Object Learning with Mutual Exclusivity Bias

Anh Thai · Ahmad Humayun · Stefan Stojanov · Zixuan Huang · Bikram Boote · James Rehg

ZoomTrack: Target-aware Non-uniform Resizing for Efficient Visual Tracking

Yutong Kou · Jin Gao · Bing Li · Gang Wang · Weiming Hu · Yizheng Wang · Liang Li

Type-to-Track: Retrieve Any Object via Prompt-based Tracking

Pha Nguyen · Kha Gia Quach · Kris Kitani · Khoa Luu

Learning Dense Flow Field for Highly-accurate Cross-view Camera Localization

Zhenbo Song · ze xianghui · Jianfeng Lu · Yujiao Shi

EgoDistill: Egocentric Head Motion Distillation for Efficient Video Understanding

Shuhan Tan · Tushar Nagarajan · Kristen Grauman

AttrSeg: Open-Vocabulary Semantic Segmentation via Attribute Decomposition-Aggregation

Chaofan Ma · Yang Yuhuan · Chen Ju · Fei Zhang · Ya Zhang · Yanfeng Wang

SOC: Semantic-Assisted Object Cluster for Referring Video Object Segmentation

Zhuoyan Luo · Yicheng Xiao · Yong Liu · Shuyan Li · Yitong Wang · Yansong Tang · Xiu Li · Yujiu Yang

FineMoGen: Fine-Grained Spatio-Temporal Motion Generation and Editing

Mingyuan Zhang · Huirong Li · Zhongang Cai · Jiawei Ren · Lei Yang · Ziwei Liu

Jigsaw: Learning to Assemble Multiple Fractured Objects

Jiaxin Lu · Yifan Sun · Qixing Huang

SLIBO-Net: Floorplan Reconstruction via Slicing Box Representation with Local Geometry Regularization

Jheng-Wei Su · Kuei-Yu Tung · Chi-Han Peng · Peter Wonka · Hung-Kuo (James) Chu

PaintSeg: Painting Pixels for Training-free Segmentation

Xiang Li · Chung-Ching Lin · Yinpeng Chen · Yinpeng Chen · Zicheng Liu · Zicheng Liu · Jinglu Wang · Rita Singh · Bhiksha Raj

An Efficient Dataset Condensation Plugin and Its Application to Continual Learning

Enneng Yang · Li Shen · Zhenyi Wang · Zhenyi Wang · Tongliang Liu · Guibing Guo

Boundary Guided Learning-Free Semantic Control with Diffusion Models

Ye Zhu · Yu Wu · Zhiwei Deng · Olga Russakovsky · Yan Yan

Lossy Image Compression with Conditional Diffusion Models

Ruihan Yang · Stephan Mandt

Robustifying Generalizable Implicit Shape Networks with a Tunable Non-Parametric Model

Amine Ouasfi · Adnane Boukhayma

Navigating the Pitfalls of Active Learning Evaluation: A Systematic Framework for Meaningful Performance Assessment

Carsten Lüth · Till Bungert · Lukas Klein · Paul Jaeger

How2comm: Communication-Efficient and Collaboration-Pragmatic Multi-Agent Perception

Dingkang Yang · Kun Yang · Yuzheng Wang · Jing Liu · Zhi Xu · Rongbin Yin · Peng Zhai · Lihua Zhang

CoDA: Collaborative Novel Box Discovery and Cross-modal Alignment for Open-vocabulary 3D Object Detection

Yang Cao · Zeng Yihan · Hang Xu · Dan Xu

Fairness Continual Learning Approach to Semantic Scene Understanding in Open-World Environments

Thanh-Dat Truong · Hoang-Quan Nguyen · Bhiksha Raj · Khoa Luu

HEDNet: A Hierarchical Encoder-Decoder Network for 3D Object Detection in Point Clouds

Gang Zhang · Chen Junnan · Guohuan Gao · Jianmin Li · Xiaolin Hu

Weakly-Supervised Concealed Object Segmentation with SAM-based Pseudo Labeling and Multi-scale Feature Grouping

Chunming He · Kai Li · Yachao Zhang · Guoxia Xu · Longxiang Tang · Yulun Zhang · Zhenhua Guo · Xiu Li

NU-MCC: Multiview Compressive Coding with Neighborhood Decoder and Repulsive UDF

Stefan Lionar · Xiangyu Xu · Min Lin · Gim Hee Lee

4D Panoptic Scene Graph Generation

Jingkang Yang · Jun CEN · WENXUAN PENG · Shuai Liu · Fangzhou Hong · Xiangtai Li · Kaiyang Zhou · Qifeng Chen · Ziwei Liu

Echoes Beyond Points: Unleashing the Power of Raw Radar Data in Multi-modality Fusion

Yang Liu · Feng Wang · Naiyan Wang · ZHAO-XIANG ZHANG

GeoCLIP: Clip-Inspired Alignment between Locations and Images for Effective Worldwide Geo-localization

Vicente Vivanco Cepeda · Gaurav Kumar Nayak · Mubarak Shah

Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation

Yuval Kirstain · Adam Polyak · Uriel Singer · Shahbuland Matiana · Joe Penna · Omer Levy

Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation

Haonan Wang · Xiaomeng Li

SNAP: Self-Supervised Neural Maps for Visual Positioning and Semantic Understanding

Paul-Edouard Sarlin · Eduard Trulls · Marc Pollefeys · Jan Hosang · Simon Lynen

Improving neural network representations using human similarity judgments

Lukas Muttenthaler · Lorenz Linhardt · Jonas Dippel · Robert Vandermeulen · Katherine Hermann · Andrew Lampinen · Simon Kornblith

Differentiable Blocks World: Qualitative 3D Decomposition by Rendering Primitives

Tom Monnier · Jake Austin · Angjoo Kanazawa · Alexei Efros · Mathieu Aubry

Jaccard Metric Losses: Optimizing the Jaccard Index with Soft Labels

Zifu Wang · Xuefei Ning · Matthew Blaschko

Template-free Articulated Neural Point Clouds for Reposable View Synthesis

Lukas Uzolas · Elmar Eisemann · Petr Kellnhofer

NeuralGF: Unsupervised Point Normal Estimation by Learning Neural Gradient Function

Qing Li · Huifang Feng · Kanle Shi · Yue Gao · Yi Fang · Yu-Shen Liu · Zhizhong Han

Circuit as Set of Points

Jialv Zou · Xinggang Wang · Jiahao Guo · Wenyu Liu · Qian Zhang · Chang Huang

Importance-aware Co-teaching for Offline Model-based Optimization

Ye Yuan · Can (Sam) Chen · Zixuan Liu · Willie Neiswanger · Xue (Steve) Liu

Machine learning detects terminal singularities

Tom Coates · Alexander Kasprzyk · Sara Veneziale

DSR: Dynamical Surface Representation as Implicit Neural Networks for Protein

Daiwen Sun · He Huang · Yao Li · Xinqi Gong · Qiwei Ye

Brant: Foundation Model for Intracranial Neural Signal

Daoze Zhang · Zhizhang Yuan · YANG YANG · Junru Chen · Jingjing Wang · Yafeng Li

An Iterative Self-Learning Framework for Medical Domain Generalization

Zhenbang Wu · Huaxiu Yao · David Liebovitz · Jimeng Sun

ResoNet: Noise-Trained Physics-Informed MRI Off-Resonance Correction

Alfredo De Goyeneche Macaya · Shreya Ramachandran · Ke Wang · Ekin Karasan · Joseph Y. Cheng · Stella X. Yu · Michael Lustig

REFINE: A Fine-Grained Medication Recommendation System Using Deep Learning and Personalized Drug Interaction Modeling

Suman Bhoi · Mong Li Lee · Wynne Hsu · Ngiap Chuan Tan

HyPoradise: An Open Baseline for Generative Speech Recognition with Large Language Models

CHEN CHEN · Yuchen Hu · Chao-Han Huck Yang · Sabato Marco Siniscalchi · Pin-Yu Chen · Eng-Siong Chng

NuTrea: Neural Tree Search for Context-guided Multi-hop KGQA

Hyeong Kyu Choi · Seunghun Lee · Jaewon Chu · Hyunwoo Kim

ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings

Shibo Hao · Tianyang Liu · Zhen Wang · Zhiting Hu

AUDIT: Audio Editing by Following Instructions with Latent Diffusion Models

Yuancheng Wang · Zeqian Ju · Xu Tan · Lei He · Zhizheng Wu · Jiang Bian · sheng zhao

Fine-grained Late-interaction Multi-modal Retrieval for Retrieval Augmented Visual Question Answering

Weizhe Lin · Jinghong Chen · Jingbiao Mei · Alexandru Coca · Bill Byrne · Bill Byrne

LLM-Pruner: On the Structural Pruning of Large Language Models

Xinyin Ma · Gongfan Fang · Xinchao Wang

Make Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning

Baohao Liao · Shaomu Tan · Christof Monz

Disentangling Voice and Content with Self-Supervision for Speaker Recognition

TIANCHI LIU · Kong Aik Lee · Qiongqiong Wang · Haizhou Li

Learning Descriptive Image Captioning via Semipermeable Maximum Likelihood Estimation

Zihao Yue · Anwen Hu · Liang Zhang · Qin Jin

Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference

Tao Lei · Junwen Bai · Siddhartha Brahma · Joshua Ainslie · Kenton Lee · Yanqi Zhou · Nan Du · Vincent Zhao · Yuexin Wu · Bo Li · Yu Zhang · Ming-Wei Chang

Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models

Pan Lu · Baolin Peng · Hao Cheng · Michel Galley · Kai-Wei Chang · Ying Nian Wu · Song-Chun Zhu · Jianfeng Gao

Evaluating and Inducing Personality in Pre-trained Language Models

Guangyuan Jiang · Manjie Xu · Song-Chun Zhu · Wenjuan Han · Chi Zhang · Yixin Zhu

RRHF: Rank Responses to Align Language Models with Human Feedback

Hongyi Yuan · Zheng Yuan · Chuanqi Tan · Wei Wang · Songfang Huang · Fei Huang

Language Models can Solve Computer Tasks

Geunwoo Kim · Pierre Baldi · Stephen McAleer

Debiased and Denoised Entity Recognition from Distant Supervision

Haobo Wang · Yiwen Dong · Ruixuan Xiao · Fei Huang · Gang Chen · Junbo Zhao

Propagating Knowledge Updates to LMs Through Distillation

Shankar Padmanabhan · Yasumasa Onoe · Michael Zhang · Greg Durrett · Eunsol Choi

On the Pareto Front of Multilingual Neural Machine Translation

Liang Chen · Shuming Ma · Dongdong Zhang · Furu Wei · Baobao Chang

Non-autoregressive Machine Translation with Probabilistic Context-free Grammar

Shangtong Gui · Chenze Shao · Zhengrui Ma · xishan zhang · Yunji Chen · Yang Feng

Aligning Language Models with Human Preferences via a Bayesian Approach

Jiashuo WANG · Haozhao Wang · Shichao Sun · Wenjie Li

DASpeech: Directed Acyclic Transformer for Fast and High-quality Speech-to-Speech Translation

Qingkai Fang · Yan Zhou · Yang Feng

LIMA: Less Is More for Alignment

Chunting Zhou · Pengfei Liu · Puxin Xu · Srinivasan Iyer · Jiao Sun · Yuning Mao · Xuezhe Ma · Avia Efrat · Ping Yu · LILI YU · Susan Zhang · Gargi Ghosh · Mike Lewis · Luke Zettlemoyer · Omer Levy

Toolformer: Language Models Can Teach Themselves to Use Tools

Timo Schick · Jane Dwivedi-Yu · Roberto Dessi · Roberta Raileanu · Maria Lomeli · Eric Hambro · Luke Zettlemoyer · Nicola Cancedda · Thomas Scialom

Can Language Models Teach? Teacher Explanations Improve Student Performance via Personalization

Swarnadeep Saha · Peter Hase · Mohit Bansal

Information Geometry of the Retinal Representation Manifold

Xuehao Ding · Dongsoo Lee · Joshua Melander · George Sivulka · Surya Ganguli · Stephen Baccus

Spiking PointNet: Spiking Neural Networks for Point Clouds

Dayong Ren · Zhe Ma · Yuanpei Chen · Weihang Peng · Xiaode Liu · Yuhan Zhang · Yufei Guo · Yufei Guo

Brain Diffusion for Visual Exploration: Cortical Discovery using Large Scale Generative Models

Andrew Luo · Maggie Henderson · Leila Wehbe · Michael Tarr

Learning Time-Invariant Representations for Individual Neurons from Population Dynamics

Lu Mi · Trung Le · Tianxing He · Eli Shlizerman · Uygar Sümbül

Brain-like Flexible Visual Inference by Harnessing Feedback Feedforward Alignment

Tahereh Toosi · Elias Issa

Trial matching: capturing variability with data-constrained spiking neural networks

Christos Sourmpis · Carl Petersen · Wulfram Gerstner · Guillaume Bellec

A Recurrent Neural Circuit Mechanism of Temporal-scaling Equivariant Representation

Junfeng Zuo · Xiao Liu · Ying Nian Wu · Si Wu · Wenhao Zhang

Meta-learning families of plasticity rules in recurrent spiking networks using simulation-based inference

Basile Confavreux · Poornima Ramesh · Pedro Goncalves · Jakob H Macke · Tim Vogels

Training biologically plausible recurrent neural networks on cognitive tasks with long-term dependencies

Wayne Soo · Vishwa Goudar · Xiao-Jing Wang

Human spatiotemporal pattern learning as probabilistic program synthesis

Tracey Mills · Josh Tenenbaum · Samuel Cheyette

A Dual-Stream Neural Network Explains the Functional Segregation of Dorsal and Ventral Visual Pathways in Human Brains

Minkyu Choi · Kuan Han · Xiaokai Wang · Yizhen Zhang · Zhongming Liu

Cinematic Mindscapes: High-quality Video Reconstruction from Brain Activity

Zijiao Chen · Jiaxin Qing · Juan Helen Zhou

Addressing the speed-accuracy simulation trade-off for adaptive spiking neurons

Luke Taylor · Andrew King · Nicol S Harper

Convolutional Neural Operators for robust and accurate learning of PDEs

Bogdan Raonic · Roberto Molinaro · Tim De Ryck · Tobias Rohner · Francesca Bartolucci · Rima Alaifari · Siddhartha Mishra · Emmanuel de Bézenac

QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning

Di Luo · Jiayu Shen · Rumen Dangovski · Marin Soljacic

Randomized Sparse Neural Galerkin Schemes for Solving Evolution Equations with Deep Networks

Jules Berman · Benjamin Peherstorfer

PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification

Qianli Shen · Wai Hoh Tang · Zhun Deng · Apostolos Psaros · Kenji Kawaguchi

Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs

Zebang Shen · Zhenfu Wang

Variational Monte Carlo on a Budget — Fine-tuning pre-trained Neural Wavefunctions

Michael Scherbela · Leon Gerard · Philipp Grohs

SE(3) Equivariant Augmented Coupling Flows

Laurence Midgley · Vincent Stimper · Javier Antorán · Emile Mathieu · Bernhard Schölkopf · José Miguel Hernández-Lobato

PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers

Phillip Lippe · Bas Veeling · Paris Perdikaris · Richard Turner · Johannes Brandstetter

EmbodiedGPT: Vision-Language Pre-Training via Embodied Chain of Thought

Yao Mu · Qinglong Zhang · Mengkang Hu · Wenhai Wang · Mingyu Ding · Jun Jin · Bin Wang · Jifeng Dai · Yu Qiao · Ping Luo

Where2Explore: Few-shot Affordance Learning for Unseen Novel Categories of Articulated Objects

Chuanruo Ning · Ruihai Wu · Haoran Lu · Kaichun Mo · Hao Dong

3D-IntPhys: Towards More Generalized 3D-grounded Visual Intuitive Physics under Challenging Scenes

Haotian Xue · Antonio Torralba · Josh Tenenbaum · Dan Yamins · Yunzhu Li · Hsiao-Yu Tung

Data Quality in Imitation Learning

Suneel Belkhale · Yuchen Cui · Dorsa Sadigh

DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models

Tsun-Hsuan Johnson Wang · Juntian Zheng · Pingchuan Ma · Yilun Du · Byungchul Kim · Andrew Spielberg · Josh Tenenbaum · Chuang Gan · Daniela Rus

Conformal Prediction for Time Series with Modern Hopfield Networks

Andreas Auer · Martin Gauch · Daniel Klotz · Sepp Hochreiter

OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling

yifan zhang · Qingsong Wen · xue wang · Weiqi Chen · Liang Sun · Zhang Zhang · Liang Wang · Rong Jin · Tieniu Tan

On the Constrained Time-Series Generation Problem

Andrea Coletta · Sriram Gopalakrishnan · Daniel Borrajo · Svitlana Vyetrenko

On the Trade-off of Intra-/Inter-class Diversity for Supervised Pre-training

Jieyu Zhang · Bohan Wang · Zhengyu Hu · Pang Wei Koh · Alexander Ratner

Data-Centric Learning from Unlabeled Graphs with Diffusion Model

Gang Liu · Eric Inae · Tong Zhao · Jiaxin Xu · Tengfei Luo · Meng Jiang

Skill-it! A data-driven skills framework for understanding and training language models

Mayee Chen · Nicholas Roberts · Kush Bhatia · Jue WANG · Ce Zhang · Ce Zhang · Frederic Sala · Christopher Ré

Generating Images with Multimodal Language Models

Jing Yu Koh · Daniel Fried · Russ Salakhutdinov

Window-Based Distribution Shift Detection for Deep Neural Networks

Guy Bar-Shalom · Yonatan Geifman · Ran El-Yaniv

Implicit Bias of Gradient Descent for Two-layer ReLU and Leaky ReLU Networks on Nearly-orthogonal Data

Yiwen Kou · Zixiang Chen · Quanquan Gu

Neural Functional Transformers

Allan Zhou · Kaien Yang · Yiding Jiang · Kaylee Burns · Winnie Xu · Samuel Sokota · J. Zico Kolter · Chelsea Finn

NAR-Former V2: Rethinking Transformer for Universal Neural Network Representation Learning

Yun Yi · Haokui Zhang · Rong Xiao · Nannan Wang · Xiaoyu Wang

Enhancing Minority Classes by Mixing: An Adaptative Optimal Transport Approach for Long-tailed Classification

Jintong Gao · He Zhao · Zhuo Li · Dandan Guo

High dimensional, tabular deep learning with an auxiliary knowledge graph

Camilo Ruiz · Hongyu Ren · Kexin Huang · Jure Leskovec

ASPEN: Breaking Operator Barriers for Efficient Parallelization of Deep Neural Networks

Jongseok Park · Kyungmin Bin · Gibum Park · Sangtae Ha · Kyunghan Lee

MeCo: Zero-Shot NAS with One Data and Single Forward Pass via Minimum Eigenvalue of Correlation

Tangyu Jiang · Haodi Wang · Rongfang Bie

Speculative Decoding with Big Little Decoder

Sehoon Kim · Karttikeya Mangalam · Suhong Moon · Jitendra Malik · Michael Mahoney · Amir Gholami · Kurt Keutzer

SUBP: Soft Uniform Block Pruning for 1$\times$N Sparse CNNs Multithreading Acceleration

JINGYANG XIANG · Siqi Li · Jun Chen · Guang Dai · Shipeng Bai · Yukai Ma · Yong Liu

Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions

Stefano Massaroli · Michael Poli · Dan Fu · Hermann Kumbong · Rom Parnichkun · David Romero · Aman Timalsina · Quinn McIntyre · Beidi Chen · Atri Rudra · Ce Zhang · Ce Zhang · Christopher Ré · Stefano Ermon · Yoshua Bengio

StableFDG: Style and Attention Based Learning for Federated Domain Generalization

Jungwuk Park · Dong-Jun Han · Jinho Kim · Shiqiang Wang · Christopher Brinton · Jaekyun Moon

SLaM: Student-Label Mixing for Distillation with Unlabeled Examples

Vasilis Kontonis · Fotis Iliopoulos · Khoa Trinh · Cenk Baykal · Gaurav Menghani · Erik Vee

Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures

Runa Eschenhagen · Alexander Immer · Richard Turner · Frank Schneider · Philipp Hennig

Accelerated Training via Incrementally Growing Neural Networks using Variance Transfer and Learning Rate Adaptation

Xin Yuan · Pedro Savarese · Michael Maire

ResMem: Learn what you can and memorize the rest

Zitong Yang · MICHAL LUKASIK · Vaishnavh Nagarajan · Zonglin Li · Ankit Rawat · Manzil Zaheer · Aditya Menon · Sanjiv Kumar

Tree-Based Diffusion Schrödinger Bridge with Applications to Wasserstein Barycenters

Maxence Noble · Valentin De Bortoli · Arnaud Doucet · Alain Durmus

Efficient Low-rank Backpropagation for Vision Transformer Adaptation

Yuedong Yang · Hung-Yueh Chiang · Guihong Li · Diana Marculescu · Radu Marculescu

Improving Few-Shot Generalization by Exploring and Exploiting Auxiliary Data

Alon Albalak · Colin Raffel · William Yang Wang

Training Transformers with 4-bit Integers

Haocheng Xi · ChangHao Li · Jianfei Chen · Jun Zhu

Critical Initialization of Wide and Deep Neural Networks using Partial Jacobians: General Theory and Applications

Darshil Doshi · Tianyu He · Andrey Gromov

Energy Transformer

Benjamin Hoover · Yuchen Liang · Bao Pham · Rameswar Panda · Hendrik Strobelt · Duen Horng Chau · Mohammed Zaki · Dmitry Krotov

Transformers are uninterpretable with myopic methods: a case study with bounded Dyck grammars

Kaiyue Wen · Yuchen Li · Bingbin Liu · Andrej Risteski

Attentive Transfer Entropy to Exploit Transient Emergence of Coupling Effect

Xiaolei Ru · XINYA ZHANG · Zijia Liu · Jack Murdoch Moore · Gang Yan

Blockwise Parallel Transformers for Large Context Models

Hao Liu · Pieter Abbeel

Transformers learn to implement preconditioned gradient descent for in-context learning

Kwangjun Ahn · Xiang Cheng · Hadi Daneshmand · Suvrit Sra

The Impact of Positional Encoding on Length Generalization in Transformers

Amirhossein Kazemnejad · Inkit Padhi · Karthikeyan Natesan Ramamurthy · Payel Das · Siva Reddy

Hierarchically Gated Recurrent Neural Network for Sequence Modeling

Zhen Qin · Songlin Yang · Yiran Zhong

Causal Interpretation of Self-Attention in Pre-Trained Transformers

Raanan Rohekar · Yaniv Gurwicz · Shami Nisimov

Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time

Zichang Liu · Aditya Desai · Fangshuo Liao · Weitao Wang · Victor Xie · Zhaozhuo Xu · Anastasios Kyrillidis · Anshumali Shrivastava

IDRNet: Intervention-Driven Relation Network for Semantic Segmentation

Zhenchao Jin · Xiaowei Hu · Lingting Zhu · Luchuan Song · Li Yuan · Lequan Yu

Frequency Domain-Based Dataset Distillation

Donghyeok Shin · Seungjae Shin · Il-chul Moon

Score-based Generative Models with Lévy Processes

EUN BI YOON · Keehun Park · Sungwoong Kim · Sungbin Lim

Hyperbolic VAE via Latent Gaussian Distributions

Seunghyuk Cho · Juyong Lee · Dongwoo Kim

Distributional Learning of Variational AutoEncoder: Application to Synthetic Data Generation

Seunghwan An · Jong-June Jeon

Unifying GANs and Score-Based Diffusion as Generative Particle Models

Jean-Yves Franceschi · Mike Gartrell · Ludovic Dos Santos · Thibaut Issenhuth · Emmanuel de Bézenac · Mickael Chen · Alain Rakotomamonjy

Formulating Discrete Probability Flow Through Optimal Transport

Pengze Zhang · Hubery Yin · Chen Li · Xiaohua Xie

Intriguing Properties of Quantization at Scale

Arash Ahmadian · Saurabh Dash · Hongyu Chen · Bharat Venkitesh · Zhen Stephen Gou · Phil Blunsom · Ahmet Üstün · Sara Hooker

SEGA: Instructing Text-to-Image Models using Semantic Guidance

Manuel Brack · Felix Friedrich · Dominik Hintersdorf · Lukas Struppek · Patrick Schramowski · Kristian Kersting

StyleDrop: Text-to-Image Synthesis of Any Style

Kihyuk Sohn · Lu Jiang · Lu Jiang · Jarred Barber · Kimin Lee · Nataniel Ruiz · Dilip Krishnan · Huiwen Chang · Yuanzhen Li · Irfan Essa · Michael Rubinstein · Yuan Hao · Glenn Entis · Irina Blok · Daniel Castro Chin

Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective

Zeyuan Yin · Eric Xing · Zhiqiang Shen

Learning Visual Prior via Generative Pre-Training

Jinheng Xie · Kai Ye · Yudong Li · Yuexiang Li · Kevin Qinghong Lin · Yefeng Zheng · Linlin Shen · Mike Zheng Shou

Latent Diffusion for Language Generation

Justin Lovelace · Varsha Kishore · Chao Wan · Eliot Shekhtman · Kilian Weinberger

Lexinvariant Language Models

Qian Huang · Eric Zelikman · Sarah Chen · Yuhuai Wu · Gregory Valiant · Percy Liang

Mix-of-Show: Decentralized Low-Rank Adaptation for Multi-Concept Customization of Diffusion Models

Yuchao Gu · Xintao Wang · Jay Zhangjie Wu · Yujun Shi · Yunpeng Chen · Zihan Fan · WUYOU XIAO · Rui Zhao · Shuning Chang · Weijia Wu · Yixiao Ge · Ying Shan · Mike Zheng Shou

Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation

Diederik Kingma · Ruiqi Gao

SyncDiffusion: Coherent Montage via Synchronized Joint Diffusions

Yuseung Lee · Kunho Kim · Hyunjin Kim · Minhyuk Sung

Grassmann Manifold Flows for Stable Shape Generation

Ryoma Yataka · Kazuki Hirashima · Masashi Shiraishi

ViCA-NeRF: View-Consistency-Aware 3D Editing of Neural Radiance Fields

Jiahua Dong · Yu-Xiong Wang

FaceDNeRF: Semantics-Driven Face Reconstruction, Prompt Editing and Relighting with Diffusion Models

Hao ZHANG · Tianyuan DAI · Yanbo Xu · Yu-Wing Tai · Chi-Keung Tang

Token-Scaled Logit Distillation for Ternary Weight Generative Language Models

Minsoo Kim · Sihwa Lee · Janghwan Lee · Sukjin Hong · Du-Seong Chang · Wonyong Sung · Jungwook Choi

Generative Neural Fields by Mixtures of Neural Implicit Functions

Tackgeun You · Mijeong Kim · Jungtaek Kim · Bohyung Han

CSLP-AE: A Contrastive Split-Latent Permutation Autoencoder Framework for Zero-Shot Electroencephalography Signal Conversion

Anders Nørskov · Alexander Neergaard Zahid · Morten Mørup

Curvature Filtrations for Graph Generative Model Evaluation

Joshua Southern · Jeremy Wayland · Michael Bronstein · Bastian Rieck

Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation

Giorgio Giannone · Akash Srivastava · Ole Winther · Faez Ahmed

MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers

LILI YU · Daniel Simig · Colin Flaherty · Armen Aghajanyan · Luke Zettlemoyer · Mike Lewis

Isometric Quotient Variational Auto-Encoders for Structure-Preserving Representation Learning

In Huh · changwook jeong · Jae Myung Choe · YOUNGGU KIM · Daesin Kim

StyleGAN knows Normal, Depth, Albedo, and More

Anand Bhattad · Daniel McKee · Derek Hoiem · David Forsyth

Debiasing Pretrained Generative Models by Uniformly Sampling Semantic Attributes

Walter Gerych · Walter Gerych · Kevin Hickey · Luke Buquicchio · Kavin Chandrasekaran · Abdulaziz Alajaji · Elke A. Rundensteiner · Emmanuel Agu

Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels

Zebin You · Yong Zhong · Fan Bao · Jiacheng Sun · Chongxuan LI · Jun Zhu

Extracting Reward Functions from Diffusion Models

Felipe Nuti · Tim Franzmeyer · João Henriques

Entropic Neural Optimal Transport via Diffusion Processes

Nikita Gushchin · Alexander Kolesov · Alexander Korotin · Dmitry Vetrov · Evgeny Burnaev

An Information-Theoretic Evaluation of Generative Models in Learning Multi-modal Distributions

Mohammad Jalali · Cheuk Ting Li · Farzan Farnia

Functional Renyi Differential Privacy for Generative Modeling

Dihong Jiang · Sun Sun · Yaoliang Yu

Augmentation-Aware Self-Supervision for Data-Efficient GAN Training

Liang Hou · Liang Hou · Qi Cao · Yige Yuan · Songtao Zhao · Chongyang Ma · Siyuan Pan · Pengfei Wan · Zhongyuan Wang · Zhongyuan Wang · Huawei Shen · Xueqi Cheng

Efficient Training of Energy-Based Models Using Jarzynski Equality

Davide Carbone · Mengjian Hua · Simon Coste · Eric Vanden-Eijnden

Flow Factorized Representation Learning

Yue Song · Andy Keller · Nicu Sebe · Max Welling

PreDiff: Precipitation Nowcasting with Latent Diffusion Models

Zhihan Gao · Xingjian Shi · Boran Han · Hao Wang · Xiaoyong Jin · Danielle Maddix · Yi Zhu · Mu Li · Yuyang (Bernie) Wang

ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation

Jiazheng Xu · Xiao Liu · Yuchen Wu · Yuxuan Tong · Qinkai Li · Ming Ding · Jie Tang · Yuxiao Dong

Scaling Riemannian Diffusion Models

Aaron Lou · Minkai Xu · Adam Farris · Stefano Ermon

SlotDiffusion: Object-Centric Generative Modeling with Diffusion Models

Ziyi Wu · Jingyu Hu · Wuyue Lu · Igor Gilitschenski · Animesh Garg

PrimDiffusion: Volumetric Primitives Diffusion for 3D Human Generation

Zhaoxi Chen · Fangzhou Hong · Haiyi Mei · Guangcong Wang · Lei Yang · Ziwei Liu

Semantic Image Synthesis with Unconditional Generator

JungWoo Chae · Hyunin Cho · Sooyeon Go · Kyungmook Choi · Youngjung Uh

GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces

Josephine Lamp · Mark Derdzinski · Christopher Hannemann · Joost van der Linden · Lu Feng · Tianhao Wang · David Evans

OpenGSL: A Comprehensive Benchmark for Graph Structure Learning

Zhou Zhiyao · Sheng Zhou · Bochao Mao · Xuanyi Zhou · Jiawei Chen · Qiaoyu Tan · Daochen Zha · Yan Feng · Chun Chen · Can Wang

On the Ability of Graph Neural Networks to Model Interactions Between Vertices

Noam Razin · Tom Verbin · Nadav Cohen

Sheaf Hypergraph Networks

Iulia Duta · Giulia Cassarà · Fabrizio Silvestri · Pietro Lió

Neural Graph Generation from Graph Statistics

Kiarash Zahirnia · Yaochen Hu · Mark Coates · Oliver Schulte

MAG-GNN: Reinforcement Learning Boosted Graph Neural Network

Lecheng Kong · Jiarui Feng · Hao Liu · Dacheng Tao · Yixin Chen · Muhan Zhang

Latent Field Discovery in Interacting Dynamical Systems with Neural Fields

Miltiadis (Miltos) Kofinas · Erik Bekkers · Naveen Nagaraja · Efstratios Gavves

A Metadata-Driven Approach to Understand Graph Neural Networks

Ting Wei Li · Qiaozhu Mei · Jiaqi Ma

Towards Label Position Bias in Graph Neural Networks

Haoyu Han · Xiaorui Liu · Feng Shi · MohamadAli Torkamani · Charu Aggarwal · Jiliang Tang

Is Distance Matrix Enough for Geometric Deep Learning?

Zian Li · Xiyuan Wang · Yinan Huang · Muhan Zhang

What functions can Graph Neural Networks compute on random graphs? The role of Positional Encoding

Nicolas Keriven · Samuel Vaiter

A graphon-signal analysis of graph neural networks

Ron Levie

Generalised f-Mean Aggregation for Graph Neural Networks

Ryan Kortvelesy · Steven Morad · Amanda Prorok

Does Invariant Graph Learning via Environment Augmentation Learn Invariance?

Yongqiang Chen · Yatao Bian · Kaiwen Zhou · Binghui Xie · Bo Han · James Cheng

Geometric Algebra Transformer

Johann Brehmer · Pim de Haan · Sönke Behrends · Taco Cohen

Layer-Neighbor Sampling --- Defusing Neighborhood Explosion in GNNs

Muhammed Fatih Balin · Ümit Çatalyürek

Zero-One Laws of Graph Neural Networks

Sam Adam-Day · Iliant · Ismail Ceylan

How Re-sampling Helps for Long-Tail Learning?

Jiang-Xin Shi · Tong Wei · Yuke Xiang · Yu-Feng Li

Intra-Modal Proxy Learning for Zero-Shot Visual Categorization with CLIP

Qi Qian · Yuanhong Xu · Juhua Hu

VoxDet: Voxel Learning for Novel Instance Detection

Bowen Li · Jiashun Wang · Yaoyu Hu · Chen Wang · Sebastian Scherer

Feature-Learning Networks Are Consistent Across Widths At Realistic Scales

Nikhil Vyas · Alexander Atanasov · Blake Bordelon · Depen Morwani · Sabarish Sainathan · Cengiz Pehlevan

Diffused Redundancy in Pre-trained Representations

Vedant Nanda · Till Speicher · John Dickerson · Krishna Gummadi · Soheil Feizi · Adrian Weller

Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization

Haitz Sáez de Ocáriz Borde · Alvaro Arroyo · Ismael Morales · Ingmar Posner · Xiaowen Dong

Connecting Multi-modal Contrastive Representations

Zehan Wang · Yang Zhao · Xize 成 · Haifeng Huang · Jiageng Liu · Aoxiong Yin · Li Tang · Linjun Li · Yongqi Wang · Ziang Zhang · Zhou Zhao

Quantifying & Modeling Multimodal Interactions: An Information Decomposition Framework

Paul Pu Liang · Yun Cheng · Xiang Fan · Chun Kai Ling · Suzanne Nie · Richard Chen · Zihao Deng · Nicholas Allen · Randy Auerbach · Faisal Mahmood · Russ Salakhutdinov · Louis-Philippe Morency

What Knowledge Gets Distilled in Knowledge Distillation?

Utkarsh Ojha · Yuheng Li · Anirudh Sundara Rajan · Yingyu Liang · Yong Jae Lee

Efficient Beam Tree Recursion

Jishnu Ray Chowdhury · Cornelia Caragea

Balancing memorization and generalization in RNNs for high performance brain-machine Interfaces

Joseph Costello · Hisham Temmar · Luis Cubillos · Matthew Mender · Dylan Wallace · Matt Willsey · Parag Patil · Cynthia Chestek

Bifurcations and loss jumps in RNN training

Lukas Eisenmann · Zahra Monfared · Niclas Göring · Daniel Durstewitz

Cognitive Steering in Deep Neural Networks via Long-Range Modulatory Feedback Connections

Talia Konkle · George Alvarez

Hardware Resilience Properties of Text-Guided Image Classifiers

Syed Talal Wasim · Kabila Haile Soboka · Abdulrahman Mahmoud · Salman Khan · David Brooks · Gu-Yeon Wei

Effective Robustness against Natural Distribution Shifts for Models with Different Training Data

Zhouxing Shi · Nicholas Carlini · Ananth Balashankar · Ludwig Schmidt · Cho-Jui Hsieh · Alex Beutel · Yao Qin

Are aligned neural networks adversarially aligned?

Nicholas Carlini · Milad Nasr · Christopher A. Choquette-Choo · Matthew Jagielski · Irena Gao · Pang Wei Koh · Daphne Ippolito · Florian Tramer · Ludwig Schmidt

HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on Text

Han Liu · Zhi Xu · Xiaotong Zhang · Feng Zhang · Fenglong Ma · Hongyang Chen · Hong Yu · Xianchao Zhang

Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings

Klim Kireev · Maksym Andriushchenko · Carmela Troncoso · Nicolas Flammarion

GradOrth: A Simple yet Efficient Out-of-Distribution Detection with Orthogonal Projection of Gradients

Sima Behpour · Thang Long Doan · Xin Li · Wenbin He · Liang Gou · Liu Ren

Robust low-rank training via approximate orthonormal constraints

Dayana Savostianova · Emanuele Zangrando · Gianluca Ceruti · Francesco Tudisco · Francesco Tudisco

Provably Bounding Neural Network Preimages

Suhas Kotha · Christopher Brix · J. Zico Kolter · Krishnamurthy Dvijotham · Huan Zhang

Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks

Zhaohan Xi · Tianyu Du · Tianyu Du · Changjiang Li · Ren Pang · Shouling Ji · Jinghui Chen · Fenglong Ma · Ting Wang

Red Teaming Deep Neural Networks with Feature Synthesis Tools

Stephen Casper · Tong Bu · Yuxiao Li · Jiawei Li · Kevin Zhang · Kaivalya Hariharan · Dylan Hadfield-Menell

Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples

Abulhair Saparov · Richard Yuanzhe Pang · Vishakh Padmakumar · Nitish Joshi · Mehran Kazemi · Najoung Kim · He He

Understanding and Improving Ensemble Adversarial Defense

Yian Deng · Tingting Mu

Robust Contrastive Language-Image Pretraining against Data Poisoning and Backdoor Attacks

Wenhan Yang · Jingdong Gao · Baharan Mirzasoleiman

Normalization-Equivariant Neural Networks with Application to Image Denoising

Sébastien Herbreteau · Emmanuel Moebel · Charles Kervrann

Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization

Mahyar Fazlyab · Taha Entesari · Aniket Roy · Rama Chellappa

IPMix: Label-Preserving Data Augmentation Method for Training Robust Classifiers

Zhenglin Huang · Xiaoan Bao · Na Zhang · Qingqi Zhang · Xiao Tu · Biao Wu · Xi Yang

Neural Image Compression: Generalization, Robustness, and Spectral Biases

Kelsey Lieberman · James Diffenderfer · Charles Godfrey · Bhavya Kailkhura

CSOT: Curriculum and Structure-Aware Optimal Transport for Learning with Noisy Labels

Wanxing Chang · Ye Shi · Jingya Wang

Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness

Ambar Pal · Jeremias Sulam · Rene Vidal

Task-Robust Pre-Training for Worst-Case Downstream Adaptation

Jianghui Wang · Yang Chen · Xingyu Xie · Cong Fang · Zhouchen Lin

Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization

Runqi Lin · Chaojian Yu · Tongliang Liu

Wasserstein distributional robustness of neural networks

Xingjian Bai · Guangyi He · Yifan Jiang · Jan Obloj

Simplicity Bias in 1-Hidden Layer Neural Networks

Depen Morwani · Jatin Batra · Prateek Jain · Praneeth Netrapalli

On the Adversarial Robustness of Out-of-distribution Generalization Models

Xin Zou · Weiwei Liu

STREAMER: Streaming Representation Learning and Event Segmentation in a Hierarchical Manner

Ramy Mounir · Sujal Vijayaraghavan · Sudeep Sarkar

CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning

Charles Guille-Escuret · Pau Rodriguez · David Vazquez · Ioannis Mitliagkas · Joao Monteiro

Mitigating the Popularity Bias of Graph Collaborative Filtering: A Dimensional Collapse Perspective

Yifei Zhang · Hao Zhu · yankai Chen · Zixing Song · Piotr Koniusz · Irwin King

Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models

Zhimin Chen · Longlong Jing · Yingwei Li · Bing Li

Three Towers: Flexible Contrastive Learning with Pretrained Image Models

Jannik Kossen · Mark Collier · Basil Mustafa · Xiao Wang · Xiaohua Zhai · Lucas Beyer · Andreas Steiner · Andreas Steiner · Jesse Berent · Rodolphe Jenatton · Effrosyni Kokiopoulou

Better Correlation and Robustness: A Distribution-Balanced Self-Supervised Learning Framework for Automatic Dialogue Evaluation

Peiwen Yuan · Xinglin Wang · Jiayi Shi · Bin Sun · Yiwei Li · Prof. Kan

Evolutionary Neural Architecture Search for Transformer in Knowledge Tracing

Shangshang Yang · Xiaoshan Yu · Ye Tian · Xueming Yan · Haiping Ma · Xingyi Zhang

Modulated Neural ODEs

Ilze Amanda Auzina · Çağatay Yıldız · Sara Magliacane · Matthias Bethge · Efstratios Gavves

Why Did This Model Forecast This Future? Information-Theoretic Saliency for Counterfactual Explanations of Probabilistic Regression Models

Chirag Raman · Alec Nonnemaker · Amelia Villegas-Morcillo · Hayley Hung · Marco Loog

The Transient Nature of Emergent In-Context Learning in Transformers

Aaditya Singh · Stephanie Chan · Ted Moskovitz · Erin Grant · Andrew Saxe · Felix Hill

Prompt-augmented Temporal Point Process for Streaming Event Sequence

Siqiao Xue · Yan Wang · Zhixuan Chu · Xiaoming Shi · Caigao JIANG · Hongyan Hao · Gangwei Jiang · Xiaoyun Feng · James Zhang · Jun Zhou

Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products

Tamas Sarlos · Xingyou Song · David Woodruff · Richard Zhang

Training Fully Connected Neural Networks is $\exists\mathbb{R}$-Complete

Daniel Bertschinger · Christoph Hertrich · Paul Jungeblut · Tillmann Miltzow · Simon Weber

Minimum norm interpolation by perceptra: Explicit regularization and implicit bias

Jiyoung Park · Ian Pelakh · Stephan Wojtowytsch

From Tempered to Benign Overfitting in ReLU Neural Networks

Guy Kornowski · Gilad Yehudai · Ohad Shamir

Implicit Bias of (Stochastic) Gradient Descent for Rank-1 Linear Neural Network

Bochen Lyu · Zhanxing Zhu

Learning in the Presence of Low-dimensional Structure: A Spiked Random Matrix Perspective

Jimmy Ba · Murat Erdogdu · Taiji Suzuki · Zhichao Wang · Denny Wu

Penalising the biases in norm regularisation enforces sparsity

Etienne Boursier · Nicolas Flammarion

Towards a Unified Framework of Contrastive Learning for Disentangled Representations

Stefan Matthes · Zhiwei Han · Hao Shen

On the spectral bias of two-layer linear networks

Aditya Vardhan Varre · Maria-Luiza Vladarean · Loucas PILLAUD-VIVIEN · Nicolas Flammarion

Don’t just prune by magnitude! Your mask topology is a secret weapon

Duc Hoang · Souvik Kundu · Shiwei Liu · Shiwei Liu · Zhangyang "Atlas" Wang

The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit

Lorenzo Noci · Chuning Li · Mufan Li · Bobby He · Thomas Hofmann · Chris Maddison · Dan Roy

Should Under-parameterized Student Networks Copy or Average Teacher Weights?

Berfin Simsek · Amire Bendjeddou · Wulfram Gerstner · Johanni Brea

Gradient-Based Feature Learning under Structured Data

Alireza Mousavi-Hosseini · Denny Wu · Taiji Suzuki · Murat Erdogdu

Minimum Description Length and Generalization Guarantees for Representation Learning

Milad Sefidgaran · Abdellatif Zaidi · Piotr Krasnowski

Partial Multi-Label Learning with Probabilistic Graphical Disambiguation

Jun-Yi Hang · Min-Ling Zhang

Causal Component Analysis

Liang Wendong · Armin Kekić · Julius von Kügelgen · Simon Buchholz · Michel Besserve · Luigi Gresele · Bernhard Schölkopf

iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models

Tianyu Chen · Kevin Bello · Bryon Aragam · Pradeep Ravikumar

Approximate Allocation Matching for Structural Causal Bandits with Unobserved Confounders

Lai Wei · Muhammad Qasim Elahi · Mahsa Ghasemi · Murat Kocaoglu

Assumption violations in causal discovery and the robustness of score matching

Francesco Montagna · Atalanti Mastakouri · Elias Eulig · Nicoletta Noceti · Lorenzo Rosasco · Dominik Janzing · Bryon Aragam · Francesco Locatello

Fair Adaptive Experiments

Waverly Wei · Xinwei Ma · Jingshen Wang

Invariant Learning via Probability of Sufficient and Necessary Causes

Mengyue Yang · Zhen Fang · Yonggang Zhang · Yali Du · Furui Liu · Jean-Francois Ton · Jianhong Wang · Jun Wang

Detecting hidden confounding in observational data using multiple environments

Rickard Karlsson · Jesse Krijthe

Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning

Wei Tang · Weijia Zhang · Min-Ling Zhang

Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars

Simon Schrodi · Danny Stoll · Binxin Ru · Rhea Sukthanker · Thomas Brox · Frank Hutter

Harnessing the power of choices in decision tree learning

Guy Blanc · Jane Lange · Chirag Pabbaraju · Colin Sullivan · Li-Yang Tan · Mo Tiwari

R-divergence for Estimating Model-oriented Distribution Discrepancy

Zhilin Zhao · Longbing Cao

On the Asymptotic Learning Curves of Kernel Ridge Regression under Power-law Decay

Yicheng Li · haobo Zhang · Qian Lin

Variational Weighting for Kernel Density Ratios

Sangwoong Yoon · Frank Park · Gunsu YUN · Iljung Kim · Yung-Kyun Noh

Kernel Quadrature with Randomly Pivoted Cholesky

Ethan Epperly · Elvira Moreno

MMD-Fuse: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting

Felix Biggs · Antonin Schrab · Arthur Gretton

Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and Reconstruction

Zeshuai Deng · Zhuokun Chen · Shuaicheng Niu · Thomas Li · Bohan Zhuang · Mingkui Tan

ALIM: Adjusting Label Importance Mechanism for Noisy Partial Label Learning

Mingyu Xu · Zheng Lian · Lei Feng · Bin Liu · Jianhua Tao

Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds

Taira Tsuchiya · Shinji Ito · Junya Honda

Diffusion-Based Probabilistic Uncertainty Estimation for Active Domain Adaptation

Zhekai Du · Jingjing Li

Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning

Pier Giuseppe Sessa · Pierre Laforgue · Nicolò Cesa-Bianchi · Andreas Krause

Towards Free Data Selection with General-Purpose Models

Yichen Xie · Mingyu Ding · Masayoshi TOMIZUKA · Wei Zhan

Alternation makes the adversary weaker in two-player games

Volkan Cevher · Ashok Cutkosky · Ali Kavis · Georgios Piliouras · Stratis Skoulakis · Luca Viano

Experimental Designs for Heteroskedastic Variance

Justin Weltz · Tanner Fiez · Alexander Volfovsky · Eric Laber · Blake Mason · houssam nassif · Lalit Jain

Scaling MLPs: A Tale of Inductive Bias

Gregor Bachmann · Sotiris Anagnostidis · Thomas Hofmann

Leveraging sparse and shared feature activations for disentangled representation learning

Marco Fumero · Florian Wenzel · Luca Zancato · Alessandro Achille · Emanuele Rodolà · Stefano Soatto · Bernhard Schölkopf · Francesco Locatello

Dynamic Tensor Decomposition via Neural Diffusion-Reaction Processes

Zheng Wang · Shikai Fang · Shibo Li · Shandian Zhe

Disentanglement via Latent Quantization

Kyle Hsu · William Dorrell · James Whittington · Jiajun Wu · Chelsea Finn

Truly Scale-Equivariant Deep Nets with Fourier Layers

Md Ashiqur Rahman · Raymond A. Yeh

Robust Concept Erasure via Kernelized Rate-Distortion Maximization

Somnath Basu Roy Chowdhury · Nicholas Monath · Kumar Avinava Dubey · Amr Ahmed · Snigdha Chaturvedi

Scale Alone Does not Improve Mechanistic Interpretability in Vision Models

Roland S. Zimmermann · Thomas Klein · Wieland Brendel

A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction

Guillaume Huguet · Alexander Tong · Edward De Brouwer · Yanlei Zhang · Guy Wolf · Ian Adelstein · Smita Krishnaswamy

How to Scale Your EMA

Dan Busbridge · Jason Ramapuram · Pierre Ablin · Tatiana Likhomanenko · Eeshan Gunesh Dhekane · Xavier Suau Cuadros · Russell Webb

AiluRus: A Scalable ViT Framework for Dense Prediction

Jin Li · Yaoming Wang · XIAOPENG ZHANG · Bowen Shi · Dongsheng Jiang · Chenglin Li · Wenrui Dai · Hongkai Xiong · Qi Tian

SOAR: Improved Indexing for Approximate Nearest Neighbor Search

Philip Sun · David Simcha · Dave Dopson · Ruiqi Guo · Sanjiv Kumar

Estimating Koopman operators with sketching to provably learn large scale dynamical systems

Giacomo Meanti · Antoine Chatalic · Vladimir Kostic · Pietro Novelli · Massimiliano Pontil · Lorenzo Rosasco

SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning

JunHoo Lee · Jayeon Yoo · Nojun Kwak

A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm

Qi Wang · Yiqin Lv · yanghe feng · Zheng Xie · Jincai Huang

Federated Conditional Stochastic Optimization

Xidong Wu · Jianhui Sun · Zhengmian Hu · Junyi Li · Aidong Zhang · Heng Huang

Mnemosyne: Learning to Train Transformers with Transformers

Deepali Jain · Krzysztof M Choromanski · Kumar Avinava Dubey · Sumeet Singh · Vikas Sindhwani · Tingnan Zhang · Jie Tan

A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm

Haizhou Shi · Hao Wang

Joint Data-Task Generation for Auxiliary Learning

Hong Chen · Xin Wang · Yuwei Zhou · Yijian Qin · Chaoyu Guan · Wenwu Zhu

CODA: Generalizing to Open and Unseen Domains with Compaction and Disambiguation

Chaoqi Chen · Luyao Tang · Yue Huang · Xiaoguang Han · Yizhou Yu

Understanding Few-Shot Learning: Measuring Task Relatedness and Adaptation Difficulty via Attributes

Minyang Hu · Hong Chang · Zong Guo · Bingpeng MA · Shiguang Shan · Xilin Chen

Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation

Yilin Lyu · Liyuan Wang · Xingxing Zhang · Zicheng Sun · Hang Su · Jun Zhu · Liping Jing

Guiding The Last Layer in Federated Learning with Pre-Trained Models

Gwen Legate · Nicolas Bernier · Lucas Page-Caccia · Edouard Oyallon · Eugene Belilovsky

Transfer Learning with Affine Model Transformation

Shunya Minami · Shunya Minami · Kenji Fukumizu · Yoshihiro Hayashi · Ryo Yoshida

Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems

Tongtong Fang · Nan Lu · Gang Niu · Masashi Sugiyama

Learning Large-scale Neural Fields via Context Pruned Meta-Learning

Jihoon Tack · Subin Kim · Sihyun Yu · Jaeho Lee · Jinwoo Shin · Jonathan Richard Schwarz

Switching Temporary Teachers for Semi-Supervised Semantic Segmentation

Jaemin Na · Jung-Woo Ha · Hyung Jin Chang · Dongyoon Han · Wonjun Hwang

Fast and Simple Spectral Clustering in Theory and Practice

Peter Macgregor

S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captions

Sangwoo Mo · Minkyu Kim · Kyungmin Lee · Jinwoo Shin

On the Exploration of Local Significant Differences For Two-Sample Test

Zhijian Zhou · Jie Ni · Jia-He Yao · Wei Gao

Optimization of Inter-group criteria for clustering with minimum size constraints

Eduardo Laber · Lucas Murtinho

A Unified Approach to Count-Based Weakly Supervised Learning

Vinay Shukla · Zhe Zeng · Kareem Ahmed · Guy Van den Broeck

Fast Rank-1 Lattice Targeted Sampling for Black-box Optimization

Yueming LYU

Block Coordinate Plug-and-Play Methods for Blind Inverse Problems

Weijie Gan · shirin shoushtari · Yuyang Hu · Jiaming Liu · Hongyu An · Ulugbek Kamilov

On the Overlooked Structure of Stochastic Gradients

Zeke Xie · Qian-Yuan Tang · Mingming Sun · Ping Li

Coordinating Distributed Example Orders for Provably Accelerated Training

A. Feder Cooper · Wentao Guo · Duc Khiem Pham · Tiancheng Yuan · Charlie Ruan · Yucheng Lu · Christopher De Sa

Debiasing Conditional Stochastic Optimization

Lie He · Shiva Kasiviswanathan

Achieving $\mathcal{O}(\epsilon^{-1.5})$ Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization

Yifan Yang · Peiyao Xiao · Kaiyi Ji

SLM: A Smoothed First-Order Lagrangian Method for Structured Constrained Nonconvex Optimization

Songtao Lu · Songtao Lu

Online Performative Gradient Descent for Learning Nash Equilibria in Decision-Dependent Games

Zihan Zhu · Ethan Fang · Zhuoran Yang

Trajectory Alignment: Understanding the Edge of Stability Phenomenon via Bifurcation Theory

Minhak Song · Chulhee Yun

Structured Neural-PI Control with End-to-End Stability and Output Tracking Guarantees

Wenqi Cui · Yan Jiang · Baosen Zhang · Yuanyuan Shi

Optimization or Architecture: How to Hack Kalman Filtering

Ido Greenberg · Netanel Yannay · Shie Mannor

Convergence Analysis of Sequential Federated Learning on Heterogeneous Data

Yipeng Li · Xinchen Lyu

First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities

Aleksandr Beznosikov · Sergey Samsonov · Marina Sheshukova · Alexander Gasnikov · Alexey Naumov · Eric Moulines

On the Generalization Error of Stochastic Mirror Descent for Quadratically-Bounded Losses: an Improved Analysis

Ta Duy Nguyen · Alina Ene · Huy Nguyen

Core-sets for Fair and Diverse Data Summarization

Sepideh Mahabadi · Stojan Trajanovski

Simple, Scalable and Effective Clustering via One-Dimensional Projections

Moses Charikar · Monika Henzinger · Lunjia Hu · Maximilian Vötsch · Erik Waingarten

Discrete-Smoothness in Online Algorithms with Predictions

Yossi Azar · Debmalya Panigrahi · Noam Touitou

T2T: From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization

Yang Li · Jinpei Guo · Runzhong Wang · Junchi Yan

DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization

Zhiqing Sun · Yiming Yang

Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions

Vladimir Feinberg · Xinyi Chen · Y. Jennifer Sun · Rohan Anil · Elad Hazan

Block Low-Rank Preconditioner with Shared Basis for Stochastic Optimization

Jui-Nan Yen · Sai Surya Duvvuri · Inderjit Dhillon · Cho-Jui Hsieh

KAKURENBO: Adaptively Hiding Samples in Deep Neural Network Training

Truong Thao Nguyen · Balazs Gerofi · Edgar Josafat Martinez-Noriega · François Trahay · Mohamed Wahib

H-nobs: Achieving Certified Fairness and Robustness in Distributed Learning on Heterogeneous Datasets

Guanqiang Zhou · Ping Xu · Ping Xu · Yue Wang · Zhi Tian

H3T: Efficient Integration of Memory Optimization and Parallelism for Large-scale Transformer Training

Yuzhong Wang · Xu Han · Weilin Zhao · Guoyang Zeng · Zhiyuan Liu · Maosong Sun

Distributed Personalized Empirical Risk Minimization

Yuyang Deng · Mohammad Mahdi Kamani · Pouria Mahdavinia · Mehrdad Mahdavi

Delayed Algorithms for Distributed Stochastic Weakly Convex Optimization

Wenzhi Gao · Qi Deng

EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning

Mohammad Mahdi Rahimi · Hasnain Irshad Bhatti · Younghyun Park · Humaira Kousar · Do-Yeon Kim · Jaekyun Moon

Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence

Yuki Takezawa · Ryoma Sato · Han Bao · Kenta Niwa · Makoto Yamada

Birder: Communication-Efficient 1-bit Adaptive Optimizer for Practical Distributed DNN Training

Hanyang Peng · Shuang Qin · Yue Yu · Jin Wang · Hui Wang · Ge Li

DropCompute: simple and more robust distributed synchronous training via compute variance reduction

Niv Giladi · Shahar Gottlieb · moran shkolnik · Asaf Karnieli · Ron Banner · Elad Hoffer · Kfir Y. Levy · Daniel Soudry

Byzantine-Tolerant Methods for Distributed Variational Inequalities

Nazarii Tupitsa · Abdulla Jasem Almansoori · Yanlin Wu · Martin Takac · Karthik Nandakumar · Samuel Horváth · Eduard Gorbunov

One Less Reason for Filter Pruning: Gaining Free Adversarial Robustness with Structured Grouped Kernel Pruning

Shaochen (Henry) Zhong · Zaichuan You · Jiamu Zhang · Sebastian Zhao · Zachary LeClaire · Zirui Liu · Daochen Zha · Vipin Chaudhary · Shuai Xu · Xia Hu

TaskMet: Task-driven Metric Learning for Model Learning

Dishank Bansal · Ricky T. Q. Chen · Mustafa Mukadam · Brandon Amos

Neural Multi-Objective Combinatorial Optimization with Diversity Enhancement

Jinbiao Chen · Zizhen Zhang · Zhiguang Cao · Yaoxin Wu · Yining Ma · Te Ye · Jiahai Wang

Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift

YUAN JIANG · Zhiguang Cao · Yaoxin Wu · Wen Song · Jie Zhang

Federated Multi-Objective Learning

Haibo Yang · Zhuqing Liu · Jia Liu · Chaosheng Dong · Michinari Momma

Geometric Analysis of Matrix Sensing over Graphs

Haixiang Zhang · Ying Chen · Javad Lavaei

On Single-Index Models beyond Gaussian Data

Aaron Zweig · Loucas PILLAUD-VIVIEN · Joan Bruna

Imbalanced Mixed Linear Regression

Pini Zilber · Boaz Nadler

Advice Querying under Budget Constraint for Online Algorithms

Ziyad Benomar · Vianney Perchet

Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation

Aniket Das · Dheeraj Nagaraj

Quantum speedups for stochastic optimization

Aaron Sidford · Chenyi Zhang

Stochastic Approximation Approaches to Group Distributionally Robust Optimization

Lijun Zhang · Peng Zhao · Zhen-Hua Zhuang · Tianbao Yang · Zhi-Hua Zhou

“Why Not Looking backward?” A Robust Two-Step Method to Automatically Terminate Bayesian Optimization

Shuang Li · Ke Li · Wei Li

Utilitarian Algorithm Configuration

Devon Graham · Kevin Leyton-Brown · Tim Roughgarden

An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization

Marco Rando · Cesare Molinari · Lorenzo Rosasco · Silvia Villa

Calibration by Distribution Matching: Trainable Kernel Calibration Metrics

Charlie Marx · Sofian Zalouk · Stefano Ermon

Flow Matching for Scalable Simulation-Based Inference

Jonas Wildberger · Maximilian Dax · Simon Buchholz · Stephen Green · Jakob H Macke · Bernhard Schölkopf

Squared Neural Families: A New Class of Tractable Density Models

Russell Tsuchida · Cheng Soon Ong · Dino Sejdinovic

Bayes beats Cross Validation: Efficient and Accurate Ridge Regression via Expectation Maximization

Shu Yu Tew · Mario Boley · Daniel Schmidt

Streaming Factor Trajectory Learning for Temporal Tensor Decomposition

Shikai Fang · Xin Yu · Shibo Li · Zheng Wang · Mike Kirby · Shandian Zhe

Pseudo-Likelihood Inference

Theo Gruner · Boris Belousov · Fabio Muratore · Daniel Palenicek · Jan Peters

Tanimoto Random Features for Scalable Molecular Machine Learning

Austin Tripp · Sergio Bacallado · Sukriti Singh · José Miguel Hernández-Lobato

Variational Gaussian processes for linear inverse problems

Thibault RANDRIANARISOA · Botond Szabo

Conditional Matrix Flows for Gaussian Graphical Models

Marcello Massimo Negri · Fabricio Arend Torres · Volker Roth

Faster Relative Entropy Coding with Greedy Rejection Coding

Gergely Flamich · Stratis Markou · José Miguel Hernández-Lobato

On the Statistical Consistency of Risk-Sensitive Bayesian Decision-Making

Prateek Jaiswal · Harsha Honnappa · Vinayak Rao

Goal-Conditioned Predictive Coding for Offline Reinforcement Learning

Zilai Zeng · Ce Zhang · Shijie Wang · Chen Sun

Residual Q-Learning: Offline and Online Policy Customization without Value

Chenran Li · Chen Tang · Haruki Nishimura · Jean Mercat · Masayoshi TOMIZUKA · Wei Zhan

Fractal Landscapes in Policy Optimization

Tao Wang · Sylvia Herbert · Sicun Gao

Truncating Trajectories in Monte Carlo Policy Evaluation: an Adaptive Approach

Riccardo Poiani · Nicole Nobili · Alberto Maria Metelli · Marcello Restelli

Sequential Preference Ranking for Efficient Reinforcement Learning from Human Feedback

Minyoung Hwang · Gunmin Lee · Hogun Kee · Chan Woo Kim · Kyungjae Lee · Songhwai Oh

Model-free Posterior Sampling via Learning Rate Randomization

Daniil Tiapkin · Denis Belomestny · Daniele Calandriello · Eric Moulines · Remi Munos · Alexey Naumov · Pierre Perrault · Michal Valko · Pierre Ménard

f-Policy Gradients: A General Framework for Goal-Conditioned RL using f-Divergences

Siddhant Agarwal · Ishan Durugkar · Peter Stone · Amy Zhang

RoboCLIP: One Demonstration is Enough to Learn Robot Policies

Sumedh Sontakke · Jesse Zhang · Séb Arnold · Karl Pertsch · Erdem Bıyık · Dorsa Sadigh · Chelsea Finn · Laurent Itti

Task-aware world model learning with meta weighting via bi-level optimization

Huining Yuan · Hongkun Dou · Xingyu Jiang · Yue Deng

Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning

Yihang Yao · ZUXIN LIU · Zhepeng Cen · Jiacheng Zhu · Wenhao Yu · Tingnan Zhang · DING ZHAO

Prediction and Control in Continual Reinforcement Learning

Nishanth Anand · Doina Precup

Hybrid Policy Optimization from Imperfect Demonstrations

Hanlin Yang · Chao Yu · peng sun · Siji Chen

Reduced Policy Optimization for Continuous Control with Hard Constraints

Shutong Ding · Jingya Wang · Yali Du · Ye Shi

Future-Dependent Value-Based Off-Policy Evaluation in POMDPs

Masatoshi Uehara · Haruka Kiyohara · Andrew Bennett · Victor Chernozhukov · Nan Jiang · Nathan Kallus · Chengchun Shi · Wen Sun

Direct Preference-based Policy Optimization without Reward Modeling

Gaon An · Junhyeok Lee · Xingdong Zuo · Norio Kosaka · Kyung-Min Kim · Hyun Oh Song

Sample Efficient Reinforcement Learning in Mixed Systems through Augmented Samples and Its Applications to Queueing Networks

Honghao Wei · Honghao Wei · Xin Liu · Weina Wang · Lei Ying

Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning

Mitsuhiko Nakamoto · Simon Zhai · Anikait Singh · Max Sobol Mark · Yi Ma · Chelsea Finn · Aviral Kumar · Sergey Levine

Optimal Treatment Allocation for Efficient Policy Evaluation in Sequential Decision Making

Ting Li · Chengchun Shi · Jianing Wang · Fan Zhou · hongtu zhu

Off-Policy Evaluation for Human Feedback

Qitong Gao · Ge Gao · Juncheng Dong · Vahid Tarokh · Min Chi · Miroslav Pajic

CORL: Research-oriented Deep Offline Reinforcement Learning Library

Denis Tarasov · Alexander Nikulin · Dmitry Akimov · Vladislav Kurenkov · Sergey Kolesnikov

Latent exploration for Reinforcement Learning

Alberto Silvio Chiappa · Alessandro Marin Vargas · Ann Huang · Alexander Mathis

Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement Learning

Changyu CHEN · Ramesha Karunasena · Thanh Nguyen · Arunesh Sinha · Pradeep Varakantham

Goal-conditioned Offline Planning from Curious Exploration

Marco Bagatella · Georg Martius

Conditional Mutual Information for Disentangled Representations in Reinforcement Learning

Mhairi Dunion · Trevor McInroe · Kevin Luck · Kevin Sebastian Luck · Josiah Hanna · Stefano Albrecht

State Regularized Policy Optimization on Data with Dynamics Shift

Zhenghai Xue · Qingpeng Cai · Shuchang Liu · Dong Zheng · Peng Jiang · Kun Gai · Bo An

Domain Adaptive Imitation Learning with Visual Observation

Sungho Choi · Seungyul Han · Woojun Kim · Jongseong Chae · Whiyoung Jung · Youngchul Sung

RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability

Chuning Zhu · Max Simchowitz · Siri Gadipudi · Abhishek Gupta

Parameterizing Non-Parametric Meta-Reinforcement Learning Tasks via Subtask Decomposition

Suyoung Lee · Myungsik Cho · Youngchul Sung

A Long $N$-step Surrogate Stage Reward for Deep Reinforcement Learning

Junmin Zhong · Ruofan Wu · Jennie Si

State Sequences Prediction via Fourier Transform for Representation Learning

Mingxuan Ye · Yufei Kuang · Jie Wang · Yang Rui · Wengang Zhou · Houqiang Li · Feng Wu

Video Prediction Models as Rewards for Reinforcement Learning

Alejandro Escontrela · Ademi Adeniji · Wilson Yan · Ajay Jain · Xue Bin Peng · Ken Goldberg · Youngwoon Lee · Danijar Hafner · Pieter Abbeel

$\texttt{TACO}$: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning

Ruijie Zheng · Xiyao Wang · Yanchao Sun · Shuang Ma · Jieyu Zhao · Huazhe Xu · Hal Daumé III · Furong Huang

For SALE: State-Action Representation Learning for Deep Reinforcement Learning

Scott Fujimoto · Wei-Di Chang · Edward Smith · Shixiang (Shane) Gu · Doina Precup · David Meger

Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards

Semih Cayci · Atilla Eryilmaz

Large Language Models can Implement Policy Iteration

Ethan Brooks · Logan Walls · Richard L Lewis · Satinder Singh

Sample Complexity of Goal-Conditioned Hierarchical Reinforcement Learning

Arnaud Robert · Ciara Pike-Burke · Aldo Faisal

Efficient Model-Free Exploration in Low-Rank MDPs

Zak Mhammedi · Adam Block · Dylan J Foster · Alexander Rakhlin

Convergence of Actor-Critic with Multi-Layer Neural Networks

Haoxing Tian · Alex Olshevsky · Yannis Paschalidis

Learning Multi-agent Behaviors from Distributed and Streaming Demonstrations

Shicheng Liu · Minghui Zhu

Zero-sum Polymatrix Markov Games: Equilibrium Collapse and Efficient Computation of Nash Equilibria

Fivos Kalogiannis · Ioannis Panageas

RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization

Siqi Shen · Chennan Ma · Chao Li · Weiquan Liu · Yongquan Fu · Songzhu Mei · Xinwang Liu · Cheng Wang

Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms

Alexander Bukharin · Yan Li · Yue Yu · Qingru Zhang · Zhehui Chen · Simiao Zuo · Chao Zhang · Songan Zhang · Tuo Zhao

AlberDICE: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation

Daiki E. Matsunaga · Jongmin Lee · Jaeseok Yoon · Stefanos Leonardos · Pieter Abbeel · Kee-Eung Kim

Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints

Soumyabrata Pal · Arun Suggala · Karthikeyan Shanmugam · Prateek Jain

Mutual-Information Regularized Multi-Agent Policy Iteration

Wang · Deheng Ye · Zongqing Lu

Selectively Sharing Experiences Improves Multi-Agent Reinforcement Learning

Matthias Gerstgrasser · Tom Danino · Sarah Keren

Multi-Step Generalized Policy Improvement by Leveraging Approximate Models

Lucas N. Alegre · Ana Bazzan · Ann Nowe · Bruno C. da Silva

Information-guided Planning: An Online Approach for Partially Observable Problems

Matheus Aparecido Do Carmo Alves · Amokh Varma · Yehia Elkhatib · Leandro Soriano Marcolino

Optimize Planning Heuristics to Rank, not to Estimate Cost-to-Goal

Leah Chrestien · Stefan Edelkamp · Antonin Komenda · Tomas Pevny

Describe, Explain, Plan and Select: Interactive Planning with LLMs Enables Open-World Multi-Task Agents

Zihao Wang · Shaofei Cai · Guanzhou Chen · Anji Liu · Xiaojian (Shawn) Ma · Yitao Liang

PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change

Karthik Valmeekam · Matthew Marquez · Alberto Olmo · Sarath Sreedharan · Subbarao Kambhampati

On Dynamic Programming Decompositions of Static Risk Measures in Markov Decision Processes

Jia Lin Hau · Erick Delage · Mohammad Ghavamzadeh · Marek Petrik

Trade-off Between Efficiency and Consistency for Removal-based Explanations

Yifan Zhang · Haowei He · Zhiquan Tan · Yang Yuan

A Privacy-Friendly Approach to Data Valuation

Jiachen (Tianhao) Wang · Yuqing Zhu · Yu-Xiang Wang · Ruoxi Jia · Prateek Mittal

Statistically Valid Variable Importance Assessment through Conditional Permutations

Ahmad CHAMMA · Denis Engemann · Bertrand Thirion

Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction

Quentin Delfosse · Hikaru Shindo · Devendra Dhami · Kristian Kersting

Feature Learning for Interpretable, Performant Decision Trees

Jack Good · Torin Kovach · Kyle Miller · Artur Dubrawski

Learning Transformer Programs

Dan Friedman · Alexander Wettig · Danqi Chen

Visual Explanations of Image-Text Representations via Multi-Modal Information Bottleneck Attribution

Ying Wang · Tim G. J. Rudner · Andrew Wilson

VeriX: Towards Verified Explainability of Deep Neural Networks

Min Wu · Haoze Wu · Clark Barrett

GRAND-SLAMIN’ Interpretable Additive Modeling with Structural Constraints

Shibal Ibrahim · Gabriel Afriat · Kayhan Behdin · Rahul Mazumder

Emergent and Predictable Memorization in Large Language Models

Stella Biderman · USVSN PRASHANTH · Lintang Sutawika · Lintang Sutawika · Hailey Schoelkopf · Quentin Anthony · Shivanshu Purohit · Edward Raff

ATMAN: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation

Björn Deiseroth · Mayukh Deb · Samuel Weinbach · Manuel Brack · Patrick Schramowski · Kristian Kersting

Interpretable Graph Networks Formulate Universal Algebra Conjectures

Francesco Giannini · Stefano Fioravanti · Oguzhan Keskin · Alisia Lupidi · Alisia Lupidi · Lucie Charlotte Magister · Pietro Lió · Pietro Barbiero

Fairly Recommending with Social Attributes: A Flexible and Controllable Optimization Approach

Jinqiu Jin · Haoxuan Li · Fuli Feng · Sihao Ding · Peng Wu · Xiangnan He

Label-Only Model Inversion Attacks via Knowledge Transfer

Bao-Ngoc Nguyen · Keshigeyan Chandrasegaran · Milad Abdollahzadeh · Ngai-Man (Man) Cheung

Perturbation Towards Easy Samples Improves Targeted Adversarial Transferability

Junqi Gao · Biqing Qi · Yao Li · Zhichang Guo · Dong Li · Yuming Xing · Dazhi Zhang

Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach

Zhimeng (Stephen) Jiang · Xiaotian Han · Hongye Jin · Guanchu Wang · Rui Chen · Na Zou · Xia Hu

Auditing Fairness by Betting

Ben Chugg · Santiago Cortes-Gomez · Bryan Wilder · Aaditya Ramdas

Mitigating Test-Time Bias for Fair Image Retrieval

Fanjie Kong · Shuai Yuan · Weituo Hao · Ricardo Henao

Counterfactually Fair Representation

Zhiqun Zuo · Mahdi Khalili · Xueru Zhang

Evaluating the Moral Beliefs Encoded in LLMs

Nino Scherrer · Claudia Shi · Amir Feder · David Blei

Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency

Xiyang Liu · Prateek Jain · Weihao Kong · Sewoong Oh · Arun Suggala

Training Private Models That Know What They Don’t Know

Stephan Rabanser · Anvith Thudi · Abhradeep Guha Thakurta · Krishnamurthy Dvijotham · Nicolas Papernot

An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions

Yingtai Xiao · Guanlin He · Danfeng Zhang · Daniel Kifer

Practical Differentially Private Hyperparameter Tuning with Subsampling

Antti Koskela · Tejas Kulkarni

A Smooth Binary Mechanism for Efficient Private Continual Observation

Joel Daniel Andersson · Rasmus Pagh

Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM

Ziba Parsons · Fei Dou · Houyi Du · Zheng Song · Jin Lu

Decision Tree for Locally Private Estimation with Public Data

Yuheng Ma · Han Zhang · Yuchao Cai · Hanfang Yang

On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence

Achraf Azize · Marc Jourdan · Aymen Al Marjani · Debabrota Basu

Adaptive Data Analysis in a Balanced Adversarial Model

Kobbi Nissim · Uri Stemmer · Eliad Tsfadia

Handling Data Heterogeneity via Architectural Design for Federated Visual Recognition

Sara Pieri · Jose Restom · Samuel Horváth · Hisham Cholakkal

Joint Attribute and Model Generalization Learning for Privacy-Preserving Action Recognition

Duo Peng · Li Xu · Qiuhong Ke · Ping Hu · Ping Hu · Jun Liu

Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners

Rachel Redberg · Antti Koskela · Yu-Xiang Wang

Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks

Jiayuan Ye · Zhenyu Zhu · Fanghui Liu · Reza Shokri · Volkan Cevher

Smooth Flipping Probability for Differential Private Sign Random Projection Methods

Ping Li · Xiaoyun Li

Faster approximate subgraph counts with privacy

Dung Nguyen · Mahantesh Halappanavar · Venkatesh Srinivasan · Venkatesh Srinivasan · Anil Vullikanti

Unbounded Differentially Private Quantile and Maximum Estimation

David Durfee

DiffAttack: Evasion Attacks Against Diffusion-Based Adversarial Purification

Mintong Kang · Dawn Song · Bo Li

RADAR: Robust AI-Text Detection via Adversarial Learning

Xiaomeng Hu · Pin-Yu Chen · Tsung-Yi Ho

Learning to Augment Distributions for Out-of-distribution Detection

Qizhou Wang · Zhen Fang · Yonggang Zhang · Feng Liu · Yixuan Li · Bo Han

Rethinking the Backward Propagation for Adversarial Transferability

Wang Xiaosen · Kangheng Tong · Kun He

Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders

Jan Dubiński · Stanisław Pawlak · Franziska Boenisch · Tomasz Trzcinski · Adam Dziedzic

Honesty Is the Best Policy: Defining and Mitigating AI Deception

Francis Ward · Francesca Toni · Francesco Belardinelli · Tom Everitt

CBD: A Certified Backdoor Detector Based on Local Dominant Probability

Zhen Xiang · Zidi Xiong · Bo Li

Domain Watermark: Effective and Harmless Dataset Copyright Protection is Closed at Hand

Junfeng Guo · Yiming Li · Lixu Wang · Shu-Tao Xia · Heng Huang · Cong Liu · Bo Li

CS-Isolate: Extracting Hard Confident Examples by Content and Style Isolation

Yexiong Lin · Yu Yao · Xiaolong Shi · Mingming Gong · Xu Shen · Dong Xu · Tongliang Liu

Human-Aligned Calibration for AI-Assisted Decision Making

Nina Corvelo Benz · Manuel Rodriguez

Improvements on Uncertainty Quantification for Node Classification via Distance Based Regularization

Russell Hart · Linlin Yu · Yifei Lou · Feng Chen

Temporal Robustness against Data poisoning

Wenxiao Wang · Soheil Feizi

D4Explainer: In-distribution Explanations of Graph Neural Network via Discrete Denoising Diffusion

Jialin Chen · Shirley Wu · Abhijit Gupta · Rex Ying

Private estimation algorithms for stochastic block models and mixture models

Hongjie Chen · Vincent Cohen-Addad · Tommaso d’Orsi · Alessandro Epasto · Jacob Imola · David Steurer · Stefan Tiegel

Active Learning-Based Species Range Estimation

Christian Lange · Elijah Cole · Grant Van Horn · Grant Horn · Oisin Mac Aodha

On the Stability-Plasticity Dilemma in Continual Meta-Learning: Theory and Algorithm

Qi CHEN · Changjian Shui · Ligong Han · Mario Marchand

Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms

Dheeraj Baby · Saurabh Garg · Tzu-Ching Yen · Sivaraman Balakrishnan · Zachary Lipton · Yu-Xiang Wang

Adversarial Self-Training Improves Robustness and Generalization for Gradual Domain Adaptation

Lianghe Shi · Weiwei Liu

On Transfer of Adversarial Robustness from Pretraining to Downstream Tasks

Laura F. Nern · Harsh Raj · Maurice André Georgi · Yash Sharma

Multiply Robust Federated Estimation of Targeted Average Treatment Effects

Larry Han · Zhu Shen · Jose Zubizarreta

Faster Query Times for Fully Dynamic $k$-Center Clustering with Outliers

Leyla Biabani · Annika Hennes · Morteza Monemizadeh · Melanie Schmidt

Strategic Distribution Shift of Interacting Agents via Coupled Gradient Flows

Lauren Conger · Franca Hoffmann · Eric Mazumdar · Lillian Ratliff

Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games

Hedi Hadiji · Sarah Sachs · Tim van Erven · Wouter Koolen

SHAP-IQ: Unified Approximation of any-order Shapley Interactions

Fabian Fumagalli · Maximilian Muschalik · Patrick Kolpaczki · Eyke Hüllermeier · Barbara Hammer

A One-Size-Fits-All Approach to Improving Randomness in Paper Assignment

Yixuan Xu · Steven Jecmen · Zimeng Song · Fei Fang

Payoff-based Learning with Matrix Multiplicative Weights in Quantum Games

Kyriakos Lotidis · Panayotis Mertikopoulos · Nicholas Bambos · Jose Blanchet

Explainable and Efficient Randomized Voting Rules

Soroush Ebadian · Aris Filos-Ratsikas · Mohamad Latifian · Nisarg Shah

$\varepsilon$-fractional core stability in Hedonic Games.

Simone Fioravanti · Michele Flammini · Bojana Kodric · Giovanna Varricchio

Improved Bayes Risk Can Yield Reduced Social Welfare Under Competition

Meena Jagadeesan · Michael Jordan · Jacob Steinhardt · Nika Haghtalab

Neural Oscillators are Universal

Samuel Lanthaler · T. Konstantin Rusch · Siddhartha Mishra

Contrastive Moments: Unsupervised Halfspace Learning in Polynomial Time

Xinyuan Cao · Santosh Vempala

Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms

Sijia Zhou · Yunwen Lei · Ata Kaban

Universality laws for Gaussian mixtures in generalized linear models

Yatin Dandi · Ludovic Stephan · Florent Krzakala · Bruno Loureiro · Lenka Zdeborová

Adaptive Principal Component Regression with Applications to Panel Data

Anish Agarwal · Keegan Harris · Justin Whitehouse · Steven Wu

Learning Exponential Families from Truncated Samples

Jane Lee · Andre Wibisono · Emmanouil Zampetakis

A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm

Ilias Diakonikolas · Daniel Kane · Jasper Lee · Ankit Pensia · Ankit Pensia · Thanasis Pittas

Two-Stage Learning to Defer with Multiple Experts

Anqi Mao · Christopher Mohri · Mehryar Mohri · Yutao Zhong

$L_2$-Uniform Stability of Randomized Learning Algorithms: Sharper Generalization Bounds and Confidence Boosting

Xiaotong Yuan · Ping Li

Minimax-Optimal Location Estimation

Shivam Gupta · Jasper Lee · Eric Price · Paul Valiant

Approximation-Generalization Trade-offs under (Approximate) Group Equivariance

Mircea Petrache · Shubhendu Trivedi

Distribution Learnability and Robustness

Shai Ben-David · Alex Bie · Gautam Kamath · Tosca Lechner

Robust covariance estimation with missing values and cell-wise contamination

Grégoire Pacreau · Karim Lounici

Demographic Parity Constrained Minimax Optimal Regression under Linear Model

Kazuto Fukuchi · Jun Sakuma

Time-Independent Information-Theoretic Generalization Bounds for SGLD

Futoshi Futami · Masahiro Fujisawa

On quantum backpropagation, information reuse, and cheating measurement collapse

Amira Abbas · Robbie King · Hsin-Yuan Huang · William J. Huggins · Ramis Movassagh · Dar Gilboa · Jarrod McClean

The Gain from Ordering in Online Learning

Vasilis Kontonis · Mingchen Ma · Christos Tzamos

Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning

Austin Xu · Andrew McRae · Jingyan Wang · Mark Davenport · Ashwin Pananjady

First- and Second-Order Bounds for Adversarial Linear Contextual Bandits

Julia Olkhovskaya · Jack Mayo · Tim van Erven · Gergely Neu · Chen-Yu Wei

Finite-Time Logarithmic Bayes Regret Upper Bounds

Alexia Atsidakou · Branislav Kveton · Sumeet Katariya · Constantine Caramanis · Sujay Sanghavi

Bandit Task Assignment with Unknown Processing Time

Shinji Ito · Daisuke Hatano · Hanna Sumita · Kei Takemura · Takuro Fukunaga · Naonori Kakimura · Ken-Ichi Kawarabayashi

Online Learning under Adversarial Nonlinear Constraints

Pavel Kolev · Georg Martius · Michael Muehlebach

Decentralized Randomly Distributed Multi-agent Multi-armed Bandit with Heterogeneous Rewards

Mengfan Xu · Diego Klabjan

On Robust Streaming for Learning with Experts: Algorithms and Lower Bounds

David Woodruff · Fred Zhang · Samson Zhou

Cascading Bandits: Optimizing Recommendation Frequency in Delayed Feedback Environments

Dairui Wang · Junyu Cao · Yan Zhang · Wei Qi

Nash Regret Guarantees for Linear Bandits

Ayush Sawarni · Ayush Sawarni · Soumyabrata Pal · Siddharth Barman

Efficient Batched Algorithm for Contextual Linear Bandits with Large Action Space via Soft Elimination

Osama Hanna · Lin Yang · Christina Fragouli

Trading-off price for data quality to achieve fair online allocation

Mathieu Molina · Nicolas Gast · Patrick Loiseau · Vianney Perchet

Context-lumpable stochastic bandits

Chung-Wei Lee · Qinghua Liu · Yasin Abbasi Yadkori · Chi Jin · Tor Lattimore · Csaba Szepesvari

When Can We Track Significant Preference Shifts in Dueling Bandits?

Joe Suk · Arpit Agarwal · Arpit Agarwal

Asymptotically Optimal Quantile Pure Exploration for Infinite-Armed Bandits

Evelyn Xiao-Yue Gong · Mark Sellke

Faster Margin Maximization Rates for Generic Optimization Methods

Guanghui Wang · Zihao Hu · Vidya Muthukumar · Jacob Abernethy

Zero-Regret Performative Prediction Under Inequality Constraints

Wenjing YAN · Xuanyu Cao

Towards Optimal Effective Resistance Estimation

Rajat Vadiraj Dwaraknath · Ishani Karmarkar · Aaron Sidford

On the Implicit Bias of Linear Equivariant Steerable Networks

Ziyu Chen · Wei Zhu

Streaming PCA for Markovian Data

Syamantak Kumar · Purnamrita Sarkar

Near-Linear Time Algorithm for the Chamfer Distance

Ainesh Bakshi · Piotr Indyk · Rajesh Jayaram · Sandeep Silwal · Erik Waingarten

First Order Stochastic Optimization with Oblivious Noise

Ilias Diakonikolas · Sushrut Karmalkar · Jong Ho Park · Christos Tzamos

On Slicing Optimality for Mutual Information

Ammar Fayad · Majd Ibrahim

Policy Gradient for Rectangular Robust Markov Decision Processes

Navdeep Kumar · Esther Derman · Matthieu Geist · Kfir Y. Levy · Shie Mannor

Performance Bounds for Policy-Based Average Reward Reinforcement Learning Algorithms

Yashaswini Murthy · Mehrdad Moharrami · R. Srikant

Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption

Yige Hong · Qiaomin Xie · Yudong Chen · Weina Wang

Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities

Donghao Ying · Yunkai Zhang · Yuhao Ding · Alec Koppel · Javad Lavaei

Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning

Gen Li · Wenhao Zhan · Jason Lee · Yuejie Chi · Yuxin Chen

Bi-Level Offline Policy Optimization with Limited Exploration

Wenzhuo Zhou

Multi-Player Zero-Sum Markov Games with Networked Separable Interactions

Chanwoo Park · Kaiqing Zhang · Asuman Ozdaglar

Responsible AI (RAI) Games and Ensembles

Yash Gupta · Runtian Zhai · Arun Suggala · Pradeep Ravikumar

Fast Optimal Locally Private Mean Estimation via Random Projections

Hilal Asi · Vitaly Feldman · Jelani Nelson · Huy Nguyen · Kunal Talwar

Unlocking Feature Visualization for Deep Network with MAgnitude Constrained Optimization

Thomas FEL · Thibaut Boissin · Victor Boutin · Agustin PICARD · Paul Novello · Julien Colin · Drew Linsley · Tom ROUSSEAU · Remi Cadene · Lore Goetschalckx · Laurent Gardes · Thomas Serre

Deep Stochastic Processes via Functional Markov Transition Operators

Jin Xu · Emilien Dupont · Kaspar Märtens · Thomas Rainforth · Yee Whye Teh

Optimal Rates for Bandit Nonstochastic Control

Y. Jennifer Sun · Stephen Newman · Elad Hazan

An Information Theory Perspective on Variance-Invariance-Covariance Regularization

Ravid Shwartz-Ziv · Randall Balestriero · Kenji Kawaguchi · Tim G. J. Rudner · Yann LeCun

Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning

Xiaojun Guo · Yifei Wang · Zeming Wei · Yisen Wang

Combining Behaviors with the Successor Features Keyboard

Wilka Carvalho Carvalho · Andre Saraiva · Angelos Filos · Andrew Lampinen · Loic Matthey · Richard L Lewis · Honglak Lee · Satinder Singh · Danilo Jimenez Rezende · Daniel Zoran

Proportional Response: Contextual Bandits for Simple and Cumulative Regret Minimization

Sanath Kumar Krishnamurthy · Ruohan Zhan · Susan Athey · Emma Brunskill

Geometric Neural Diffusion Processes

Emile Mathieu · Vincent Dutordoir · Michael Hutchinson · Valentin De Bortoli · Yee Whye Teh · Richard Turner

VanillaNet: the Power of Minimalism in Deep Learning

Hanting Chen · Yunhe Wang · Jianyuan Guo · Dacheng Tao

Neural Processes with Stability

Huafeng Liu · Liping Jing · Jian Yu

Does Visual Pretraining Help End-to-End Reasoning?

Chen Sun · Calvin Luo · Xingyi Zhou · Anurag Arnab · Cordelia Schmid

Episodic Multi-Task Learning with Heterogeneous Neural Processes

Jiayi Shen · Jiayi Shen · Xiantong Zhen · Qi Wang · Marcel Worring

Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes

Connor Toups · Rishi Bommasani · Kathleen Creel · Sarah Bana · Dan Jurafsky · Percy Liang

Networks are Slacking Off: Understanding Generalization Problem in Image Deraining

Jinjin Gu · Xianzheng Ma · Xiangtao Kong · Yu Qiao · Chao Dong

Reward Imputation with Sketching for Contextual Batched Bandits

Xiao Zhang · Ninglu Shao · Zihua Si · Jun Xu · Wenhan Wang · Hanjing Su · Ji-Rong Wen

Optimal Transport for Treatment Effect Estimation

Hao Wang · Jiajun Fan · Zhichao Chen · Haoxuan Li · Weiming Liu · Tianqiao Liu · Quanyu Dai · Yichao Wang · Zhenhua Dong · Ruiming Tang

Crystal Structure Prediction by Joint Equivariant Diffusion

Rui Jiao · Wenbing Huang · Peijia Lin · Jiaqi Han · Pin Chen · Yutong Lu · Yang Liu

DesCo: Learning Object Recognition with Rich Language Descriptions

Liunian Li · Zi-Yi Dou · Nanyun Peng · Kai-Wei Chang

MGDD: A Meta Generator for Fast Dataset Distillation

Songhua Liu · Xinchao Wang

LLMScore: Unveiling the Power of Large Language Models in Text-to-Image Synthesis Evaluation

Yujie Lu · Xianjun Yang · Xiujun Li · Xin Eric Wang · William Yang Wang

Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent

Giannis Daras · Yuval Dagan · Alex Dimakis · Constantinos Daskalakis

Recaptured Raw Screen Image and Video Demoiréing via Channel and Spatial Modulations

Yijia Cheng · Yijia Cheng · Xin Liu · Jingyu Yang

Adaptive Privacy Composition for Accuracy-first Mechanisms

Ryan Rogers · Gennady Samorodnitsk · Steven Wu · Aaditya Ramdas

Fast Attention Requires Bounded Entries

Josh Alman · Zhao Song

Understanding the Limitations of Deep Models for Molecular property prediction: Insights and Solutions

Jun Xia · Lecheng Zhang · Xiao Zhu · Yue Liu · Zhangyang Gao · Bozhen Hu · Cheng Tan · Jiangbin Zheng · Siyuan Li · Stan Z. Li

Alignment with human representations supports robust few-shot learning

Ilia Sucholutsky · Tom Griffiths

Optimal Preconditioning and Fisher Adaptive Langevin Sampling

Michalis Titsias

A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation

Thomas FEL · Victor Boutin · Louis Béthune · Louis Béthune · Remi Cadene · Mazda Moayeri · Léo Andéol · Mathieu Chalvidal · Thomas Serre

C-Disentanglement: Discovering Causally-Independent Generative Factors under an Inductive Bias of Confounder

Xiaoyu Liu · Jiaxin Yuan · Bang An · Yuancheng Xu · Yifan Yang · Furong Huang

Controlling Text-to-Image Diffusion by Orthogonal Finetuning

Zeju Qiu · Weiyang Liu · Haiwen Feng · Yuxuan Xue · Yao Feng · Zhen Liu · Dan Zhang · Adrian Weller · Bernhard Schölkopf

Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks

Ryan Sullivan · Akarsh Kumar · Shengyi Huang · John Dickerson · Joseph Suarez

Non-stationary Experimental Design under Linear Trends

David Simchi-Levi · Chonghuan Wang · Zeyu Zheng

Anytime-Competitive Reinforcement Learning with Policy Prior

Jianyi Yang · Pengfei Li · Tongxin Li · Adam Wierman · Shaolei Ren

Corruption-Robust Offline Reinforcement Learning with General Function Approximation

Chenlu Ye · Rui Yang · Quanquan Gu · Tong Zhang

Human-like Few-Shot Learning via Bayesian Reasoning over Natural Language

Kevin Ellis

Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling

Haotao Wang · Ziyu Jiang · Yuning You · Yan Han · Gaowen Liu · Jayanth Srinivasa · Ramana Kompella · Zhangyang "Atlas" Wang

Goal Driven Discovery of Distributional Differences via Language Descriptions

Ruiqi Zhong · Peter Zhang · Steve Li · Jinwoo Ahn · Dan Klein · Jacob Steinhardt

Compositional Generalization from First Principles

Thaddäus Wiedemer · Prasanna Mayilvahanan · Matthias Bethge · Wieland Brendel

Randomized and Deterministic Maximin-share Approximations for Fractionally Subadditive Valuations

Hannaneh Akrami · Kurt Mehlhorn · Masoud Seddighin · Golnoosh Shahkarami

Protein Design with Guided Discrete Diffusion

Nate Gruver · Samuel Stanton · Nathan Frey · Tim G. J. Rudner · Isidro Hotzel · Julien Lafrance-Vanasse · Arvind Rajpal · Kyunghyun Cho · Andrew Wilson

SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Process

Mengyu Wang · Henghui Ding · Jun Hao Liew · Jiajun Liu · Yao Zhao · Yunchao Wei

Sub-optimality of the Naive Mean Field approximation for proportional high-dimensional Linear Regression

Jiaze Qiu

Fairness-guided Few-shot Prompting for Large Language Models

Huan Ma · Changqing Zhang · Yatao Bian · Lemao Liu · Zhirui Zhang · Peilin Zhao · Shu Zhang · Huazhu Fu · Qinghua Hu · Bingzhe Wu

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Creative AI Session 2

Jean Oh · Isabelle Guyon

10:45 AM - 2:15 PM

10 Events in this session

Kiss/Crash

Adam Cole

Blabrecs: An AI-Based Game of Nonsense Word Creation

Isaac Karth · Max Kreminski

Androgynous and Mixed Race Human Face

Eunsu Kang

Voice Scroll

David R Rokeby

The WHOOPS! Gallery: An Intersection of AI, Creativity, and the Unusual

Jack Hessel · · Yonatan Bitton · Nitzan Bitton Guetta · Yuval Elovici

Visions of Resilience: Augmented Diversity

Ninon Lizé Masclef

salad bowl

Creating playful comics together with AI

AI Applications to Illustrate Native American Arts: Birdsongs: Using Transfer Learning to Augment Image Generation Models

Kimberly Mann Bruch

Visualising AI

Emma Yousif

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Invited Talk

Beyond Scaling Panel

Alexander Rush · Aakanksha Chowdhery · Angela Fan · Percy Liang · Jie Tang

2:15 PM - 3:15 PM

Sasha Rush - Speaker Bio

Alexander "Sasha" Rush is an Associate Professor at Cornell Tech and a researcher at Hugging Face. His research interest is in the study of language models with applications in controllable text generation, efficient inference, and applications in summarization and information extraction. In addition to research, he has written several popular open-source software projects supporting NLP research, programming for deep learning, and virtual academic conferences. His projects have received paper and demo awards at major NLP, visualization, and hardware conferences, an NSF Career Award and Sloan Fellowship. He tweets at @srush_nlp.

... more

Aakanksha Chowdhery - Speaker Bio

Aakanksha led the effort on training large language models at Google Brain which led to the 540B PaLM model. Aakanksha has also been a core member of the Pathways project at Google. Prior to joining Google, Aakanksha led interdisciplinary teams at Microsoft Research and Princeton University across machine learning, distributed systems and networking. Aakanksha completed her PhD from Stanford University and was awarded the Paul Baran Marconi Young Scholar Award for outstanding scientific contributions in her doctoral thesis.

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Angela Fan - Speaker Bio

Angela Fan is currently a research scientist at Meta AI focusing on large language models. Previously, Angela worked on machine translation for text and speech, including projects such as No Language Left Behind and Beyond English-Centric Multilingual Translation. Before that, Angela was a research engineer and did her PhD at INRIA Nancy, where she focused on text generation.

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Percy Liang - Speaker Bio

Percy Liang is an Assistant Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011). His research spans machine learning and natural language processing, with the goal of developing trustworthy agents that can communicate effectively with people and improve over time through interaction. Specific topics include question answering, dialogue, program induction, interactive learning, and reliable machine learning. His awards include the IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), and a Microsoft Research Faculty Fellowship (2014).

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Jie Tang - Speaker Bio

Jie Tang is a WeBank Chair Professor of Computer Science at Tsinghua University. He is a Fellow of the ACM, a Fellow of AAAI, and a Fellow of IEEE. His interest is artificial general intelligence (AGI). His research received the SIGKDD Test-of-Time Award (10-year Best Paper). He also received the SIGKDD Service Award. Recently, he puts all efforts into Large Language Models (LLMs): GLM, ChatGLM, etc.

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Oral

Oral 4B Datasets & Benchmarks

3:30 PM - 4:30 PM

4 Events in this session

Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the Mediterranean

Spyridon Kondylatos · Ioannis Prapas · Gustau Camps-Valls · Ioannis Papoutsis

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation

Sungduk Yu · Walter Hannah · Liran Peng · Jerry Lin · Mohamed Aziz Bhouri · Ritwik Gupta · Björn Lütjens · Justus C. Will · Gunnar Behrens · Julius Busecke · Nora Loose · Charles Stern · Tom Beucler · Bryce Harrop · Benjamin Hillman · Andrea Jenney · Savannah L. Ferretti · Nana Liu · Animashree Anandkumar · Noah Brenowitz · Veronika Eyring · Nicholas Geneva · Pierre Gentine · Stephan Mandt · Jaideep Pathak · Akshay Subramaniam · Carl Vondrick · Rose Yu · Laure Zanna · Tian Zheng · Ryan Abernathey · Fiaz Ahmed · David Bader · Pierre Baldi · Elizabeth Barnes · Christopher Bretherton · Peter Caldwell · Wayne Chuang · Yilun Han · YU HUANG · Fernando Iglesias-Suarez · Sanket Jantre · Karthik Kashinath · Marat Khairoutdinov · Thorsten Kurth · Nicholas Lutsko · Po-Lun Ma · Griffin Mooers · J. David Neelin · David Randall · Sara Shamekh · Mark Taylor · Nathan Urban · Janni Yuval · Guang Zhang · Mike Pritchard

Quilt-1M: One Million Image-Text Pairs for Histopathology

Wisdom Ikezogwo · Saygin Seyfioglu · Fatemeh Ghezloo · Dylan Geva · Fatwir Sheikh Mohammed · Pavan Kumar Anand · Ranjay Krishna · Linda Shapiro

BEDD: The MineRL BASALT Evaluation and Demonstrations Dataset for Training and Benchmarking Agents that Solve Fuzzy Tasks

Stephanie Milani · Anssi Kanervisto · Karolis Ramanauskas · Sander Schulhoff · Brandon Houghton · Rohin Shah

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Oral

Oral 4C COT/reasoning

3:30 PM - 4:30 PM

4 Events in this session

Why think step by step? Reasoning emerges from the locality of experience

Ben Prystawski · Michael Li · Noah Goodman

Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Shunyu Yao · Dian Yu · Jeffrey Zhao · Izhak Shafran · Tom Griffiths · Yuan Cao · Karthik Narasimhan

Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection

Yu Bai · Fan Chen · Huan Wang · Caiming Xiong · Song Mei

Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective

Guhao Feng · Bohang Zhang · Yuntian Gu · Haotian Ye · Di He · Liwei Wang

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Oral

Oral 4A Optimization

3:30 PM - 4:30 PM

4 Events in this session

A Single-Loop Accelerated Extra-Gradient Difference Algorithm with Improved Complexity Bounds for Constrained Minimax Optimization

Yuanyuan Liu · Fanhua Shang · Weixin An · Junhao Liu · Hongying Liu · Zhouchen Lin

Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models

Alex Damian · Eshaan Nichani · Rong Ge · Jason Lee

Generalizing Nonlinear ICA Beyond Structural Sparsity

Yujia Zheng · Kun Zhang

Fine-Tuning Language Models with Just Forward Passes

Sadhika Malladi · Tianyu Gao · Eshaan Nichani · Alex Damian · Jason Lee · Danqi Chen · Sanjeev Arora

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Poster

Poster Session 4

5:00 PM - 7:00 PM

588 Events in this session

Predicting a Protein's Stability under a Million Mutations

Jeffrey Ouyang-Zhang · Daniel Diaz · Adam Klivans · Philipp Kraehenbuehl

Full-Atom Protein Pocket Design via Iterative Refinement

ZAIXI ZHANG · Zepu Lu · Hao Zhongkai · Marinka Zitnik · Qi Liu

3D molecule generation by denoising voxel grids

Pedro O. Pinheiro · Joshua Rackers · Joseph Kleinhenz · Michael Maser · Omar Mahmood · Andrew Watkins · Stephen Ra · Vishnu Sresht · Saeed Saremi

Injecting Multimodal Information into Rigid Protein Docking via Bi-level Optimization

Ruijia Wang · YiWu Sun · Yujie Luo · Shaochuan Li · Cheng Yang · Xingyi Cheng · Hui Li · Chuan Shi · Le Song

AVIDa-hIL6: A Large-Scale VHH Dataset Produced from an Immunized Alpaca for Predicting Antigen-Antibody Interactions

Hirofumi Tsuruta · Hiroyuki Yamazaki · Ryota Maeda · Ryotaro Tamura · Jennifer Wei · Zelda Mariet · Poomarin Phloyphisut · Hidetoshi Shimokawa · Joseph R. Ledsam · Lucy Colwell · Akihiro Imura

Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the Mediterranean

Spyridon Kondylatos · Ioannis Prapas · Gustau Camps-Valls · Ioannis Papoutsis

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation

A Hierarchical Spatial Transformer for Massive Point Samples in Continuous Space

Wenchong He · Zhe Jiang · Tingsong Xiao · Zelin Xu · Shigang Chen · Ronald Fick · MILES MEDINA · Christine Angelini

Differentiable Registration of Images and LiDAR Point Clouds with VoxelPoint-to-Pixel Matching

Junsheng Zhou · Baorui Ma · Wenyuan Zhang · Yi Fang · Yu-Shen Liu · Zhizhong Han

PanoGen: Text-Conditioned Panoramic Environment Generation for Vision-and-Language Navigation

Jialu Li · Mohit Bansal

3D-LLM: Injecting the 3D World into Large Language Models

Yining Hong · Haoyu Zhen · Peihao Chen · Shuhong Zheng · Yilun Du · Zhenfang Chen · Chuang Gan

PolyDiffuse: Polygonal Shape Reconstruction via Guided Set Diffusion Models

Jiacheng Chen · Ruizhi Deng · Ruizhi Deng · Yasutaka Furukawa

Context-PIPs: Persistent Independent Particles Demands Spatial Context Features

Weikang Bian · Zhaoyang Huang · Zhaoyang Huang · Xiaoyu Shi · Yitong Dong · Yijin Li · Hongsheng Li

Hierarchical Integration Diffusion Model for Realistic Image Deblurring

Zheng Chen · Zheng Chen · Yulun Zhang · Ding Liu · bin xia · Jinjin Gu · Linghe Kong · Xin Yuan

Unsupervised Image Denoising with Score Function

Yutong Xie · Mingze Yuan · Bin Dong · Quanzheng Li

SmooSeg: Smoothness Prior for Unsupervised Semantic Segmentation

Mengcheng Lan · Xinjiang Wang · Yiping Ke · Jiaxing Xu · Litong Feng · Wayne Zhang

Decompose Novel into Known: Part Concept Learning For 3D Novel Class Discovery

Tingyu Weng · Jun Xiao · Haiyong Jiang

LMC: Large Model Collaboration with Cross-assessment for Training-Free Open-Set Object Recognition

Haoxuan Qu · Xiaofei Hui · Yujun Cai · Jun Liu

Equivariant Single View Pose Prediction Via Induced and Restriction Representations

Owen Howell · David Klee · Ondrej Biza · Linfeng Zhao · Robin Walters

Towards Efficient and Accurate Winograd Convolution via Full Quantization

Tianqi Chen · Weixiang Xu · Weihan Chen · Peisong Wang · Jian Cheng

GMSF: Global Matching Scene Flow

Yushan Zhang · Johan Edstedt · Bastian Wandt · Per-Erik Forssen · Maria Magnusson · Michael Felsberg

Text Promptable Surgical Instrument Segmentation with Vision-Language Models

Zijian Zhou · Oluwatosin Alabi · Meng Wei · Tom Vercauteren · Miaojing Shi

Non-Rigid Shape Registration via Deep Functional Maps Prior

Puhua Jiang · Mingze Sun · Ruqi Huang

Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry

Yong-Hyun Park · Mingi Kwon · Jaewoong Choi · Junghyo Jo · Youngjung Uh

A Partially-Supervised Reinforcement Learning Framework for Visual Active Search

Anindya Sarkar · Nathan Jacobs · Yevgeniy Vorobeychik

Rank-DETR for High Quality Object Detection

Yifan Pu · Weicong Liang · Yiduo Hao · YUHUI YUAN · Yukang Yang · Chao Zhang · Han Hu · Gao Huang

VisionLLM: Large Language Model is also an Open-Ended Decoder for Vision-Centric Tasks

Wenhai Wang · Zhe Chen · Xiaokang Chen · Jiannan Wu · Xizhou Zhu · Gang Zeng · Ping Luo · Tong Lu · Jie Zhou · Yu Qiao · Jifeng Dai

DiViNeT: 3D Reconstruction from Disparate Views using Neural Template Regularization

Aditya Vora · Akshay Gadi Patil · Hao Zhang

PanoGRF: Generalizable Spherical Radiance Fields for Wide-baseline Panoramas

Zheng Chen · Yan-Pei Cao · Yuan-Chen Guo · Chen Wang · Ying Shan · Song-Hai Zhang

Chatting Makes Perfect: Chat-based Image Retrieval

Matan Levy · Rami Ben-Ari · Nir Darshan · Dani Lischinski

PyNeRF: Pyramidal Neural Radiance Fields

Haithem Turki · Michael Zollhöfer · Christian Richardt · Deva Ramanan

Depth-discriminative Metric Learning for Monocular 3D Object Detection

Wonhyeok Choi · Mingyu Shin · Sunghoon Im

Inner-Outer Aware Reconstruction Model for Monocular 3D Scene Reconstruction

Yu-Kun Qiu · Guo-Hao Xu · Wei-Shi Zheng

Diversifying Spatial-Temporal Perception for Video Domain Generalization

Kun-Yu Lin · Jia-Run Du · Yipeng Gao · Jiaming Zhou · Wei-Shi Zheng

Segment Everything Everywhere All at Once

Xueyan Zou · Jianwei Yang · Hao Zhang · Feng Li · Linjie Li · Jianfeng Wang · Lijuan Wang · Jianfeng Gao · Yong Jae Lee

Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly Detection

Ruiying Lu · YuJie Wu · Long Tian · Dongsheng Wang · Bo Chen · Xiyang Liu · Ruimin Hu

UP-NeRF: Unconstrained Pose Prior-Free Neural Radiance Field

Injae Kim · Minhyuk Choi · Hyunwoo Kim

Detection Based Part-level Articulated Object Reconstruction from Single RGBD Image

Yuki Kawana · Tatsuya Harada

Towards Robust and Expressive Whole-body Human Pose and Shape Estimation

Hui En Pang · Zhongang Cai · Lei Yang · Qingyi Tao · Zhonghua Wu · Tianwei Zhang · Ziwei Liu

PUCA: Patch-Unshuffle and Channel Attention for Enhanced Self-Supervised Image Denoising

Hyemi Jang · Junsung Park · Dahuin Jung · Jaihyun Lew · Ho Bae · Sungroh Yoon

ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation

Shuyang Sun · WEIJUN WANG · Andrew Howard · Qihang Yu · Philip Torr · Liang-Chieh Chen

Improving CLIP Training with Language Rewrites

Lijie Fan · Dilip Krishnan · Phillip Isola · Dina Katabi · Yonglong Tian

MomentDiff: Generative Video Moment Retrieval from Random to Real

Pandeng Li · Chen-Wei Xie · Hongtao Xie · Liming Zhao · Lei Zhang · Yun Zheng · Deli Zhao · Yongdong Zhang

$p$-Poisson surface reconstruction in curl-free flow from point clouds

Yesom Park · Taekyung Lee · Jooyoung Hahn · Myungjoo Kang

ClusterFomer: Clustering As A Universal Visual Learner

James Liang · Yiming Cui · Qifan Wang · Tong Geng · Wenguan Wang · Dongfang Liu

Symbol-LLM: Leverage Language Models for Symbolic System in Visual Human Activity Reasoning

Xiaoqian Wu · Yong-Lu Li · Jianhua Sun · Cewu Lu

Dynamo-Depth: Fixing Unsupervised Depth Estimation for Dynamical Scenes

Yihong Sun · Bharath Hariharan

BiMatting: Efficient Video Matting via Binarization

Haotong Qin · Lei Ke · Xudong Ma · Martin Danelljan · Yu-Wing Tai · Chi-Keung Tang · Xianglong Liu · Fisher Yu

Dataset Diffusion: Diffusion-based Synthetic Data Generation for Pixel-Level Semantic Segmentation

Quang Nguyen · Truong Vu · Truong Vu · Anh Tran · Khoi Nguyen

RayDF: Neural Ray-surface Distance Fields with Multi-view Consistency

Zhuoman Liu · Bo Yang · Yan Luximon · Ajay Kumar · Jinxi Li

Self-Supervised Visual Acoustic Matching

Arjun Somayazulu · Changan Chen · Kristen Grauman

CoDet: Co-occurrence Guided Region-Word Alignment for Open-Vocabulary Object Detection

Chuofan Ma · Yi Jiang · Xin Wen · Zehuan Yuan · Xiaojuan Qi

Structural Pruning for Diffusion Models

Gongfan Fang · Xinyin Ma · Xinchao Wang

Enhancing Motion Deblurring in High-Speed Scenes with Spike Streams

Shiyan Chen · Jiyuan Zhang · Yajing Zheng · Tiejun Huang · Zhaofei Yu

FlowCam: Training Generalizable 3D Radiance Fields without Camera Poses via Pixel-Aligned Scene Flow

Cameron Smith · Yilun Du · Ayush Tewari · Vincent Sitzmann

LayoutGPT: Compositional Visual Planning and Generation with Large Language Models

Weixi Feng · Wanrong Zhu · Tsu-Jui Fu · Varun Jampani · Arjun Akula · Xuehai He · S Basu · Xin Eric Wang · William Yang Wang

Towards Distribution-Agnostic Generalized Category Discovery

Jianhong Bai · Zuozhu Liu · Hualiang Wang · Ruizhe Chen · Lianrui Mu · Xiaomeng Li · Joey Tianyi Zhou · YANG FENG · Jian Wu · Haoji Hu

Look Ma, No Hands! Agent-Environment Factorization of Egocentric Videos

Matthew Chang · Aditya Prakash · Saurabh Gupta

Active Reasoning in an Open-World Environment

Manjie Xu · Guangyuan Jiang · Wei Liang · Chi Zhang · Yixin Zhu

Quilt-1M: One Million Image-Text Pairs for Histopathology

Wisdom Ikezogwo · Saygin Seyfioglu · Fatemeh Ghezloo · Dylan Geva · Fatwir Sheikh Mohammed · Pavan Kumar Anand · Ranjay Krishna · Linda Shapiro

L-CAD: Language-based Colorization with Any-level Descriptions using Diffusion Priors

zheng chang · Shuchen Weng · Peixuan Zhang · Yu Li · Si Li · Boxin Shi

A case for reframing automated medical image classification as segmentation

Sarah Hooper · Mayee Chen · Khaled Saab · Kush Bhatia · Curtis Langlotz · Christopher Ré

A Unified Conditional Framework for Diffusion-based Image Restoration

Yi Zhang · Xiaoyu Shi · Dasong Li · Xiaogang Wang · Jian Wang · Hongsheng Li

3D Copy-Paste: Physically Plausible Object Insertion for Monocular 3D Detection

Yunhao Ge · Hong-Xing Yu · Cheng Zhao · Yuliang Guo · Xinyu Huang · Liu Ren · Laurent Itti · Jiajun Wu

Binary Radiance Fields

Seungjoo Shin · Jaesik Park

Continuous Parametric Optical Flow

Jianqin Luo · Zhexiong Wan · yuxin mao · Bo Li · Yuchao Dai

Puzzlefusion: Unleashing the Power of Diffusion Models for Spatial Puzzle Solving

Sepidehsadat (Sepid) Hossieni · Mohammad Amin Shabani · Saghar Irandoust · Yasutaka Furukawa

Towards Higher Ranks via Adversarial Weight Pruning

Yuchuan Tian · Hanting Chen · Tianyu Guo · Chao Xu · Yunhe Wang

Hyperbolic Space with Hierarchical Margin Boosts Fine-Grained Learning from Coarse Labels

Shu-Lin Xu · Yifan Sun · Faen Zhang · Anqi Xu · Xiu-Shen Wei · Yi Yang

FourierHandFlow: Neural 4D Hand Representation Using Fourier Query Flow

Jihyun Lee · Junbong Jang · Donghwan Kim · Minhyuk Sung · Tae-Kyun Kim

DiffUTE: Universal Text Editing Diffusion Model

Haoxing Chen · Zhuoer Xu · Zhangxuan Gu · jun lan · 行郑 · Yaohui Li · Changhua Meng · Huijia Zhu · Weiqiang Wang

SE(3) Diffusion Model-based Point Cloud Registration for Robust 6D Object Pose Estimation

Haobo Jiang · Mathieu Salzmann · Zheng Dang · Jin Xie · Jian Yang

LightSpeed: Light and Fast Neural Light Fields on Mobile Devices

Aarush Gupta · Junli Cao · Chaoyang Wang · Ju Hu · Sergey Tulyakov · Jian Ren · László Jeni

Deep Patch Visual Odometry

Zachary Teed · Lahav Lipson · Jia Deng

Self-Chained Image-Language Model for Video Localization and Question Answering

Shoubin Yu · Jaemin Cho · Prateek Yadav · Mohit Bansal

Scale-Space Hypernetworks for Efficient Biomedical Image Analysis

Jose Javier Gonzalez Ortiz · John Guttag · Adrian Dalca

DropPos: Pre-Training Vision Transformers by Reconstructing Dropped Positions

Haochen Wang · Junsong Fan · Yuxi Wang · Kaiyou Song · Tong Wang · ZHAO-XIANG ZHANG

Segment Anything in High Quality

Lei Ke · Mingqiao Ye · Martin Danelljan · Yifan liu · Yu-Wing Tai · Chi-Keung Tang · Fisher Yu

Chanakya: Learning Runtime Decisions for Adaptive Real-Time Perception

Anurag Ghosh · Vaibhav Balloli · Akshay Nambi · Aditya Singh · Tanuja Ganu

ATTA: Anomaly-aware Test-Time Adaptation for Out-of-Distribution Detection in Segmentation

Zhitong Gao · Shipeng Yan · Xuming He

Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusion

Yash Bhalgat · Iro Laina · João Henriques · Andrea Vedaldi · Andrew Zisserman

DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation

Kaipeng Zheng · Huishuai Zhang · Weiran Huang

What You See is What You Read? Improving Text-Image Alignment Evaluation

Michal Yarom · Yonatan Bitton · Soravit Changpinyo · Roee Aharoni · Jonathan Herzig · Oran Lang · Eran Ofek · Idan Szpektor

MarioGPT: Open-Ended Text2Level Generation through Large Language Models

Shyam Sudhakaran · Miguel González-Duque · Matthias Freiberger · Claire Glanois · Elias Najarro · Sebastian Risi

Boosting Learning for LDPC Codes to Improve the Error-Floor Performance

Hee-Youl Kwak · Dae-Young Yun · Yongjune Kim · Sang-Hyo Kim · Jong-Seon No

ANPL: Towards Natural Programming with Interactive Decomposition

Di Huang · Ziyuan Nan · Xing Hu · Pengwei Jin · Shaohui Peng · Yuanbo Wen · Rui Zhang · Zidong Du · Qi Guo · Yewen Pu · Yunji Chen

CELLE-2: Translating Proteins to Pictures and Back with a Bidirectional Text-to-Image Transformer

Emaad Khwaja · Yun Song · Aaron Agarunov · Bo Huang

DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets

Lazar Atanackovic · Alexander Tong · Bo Wang · Leo J Lee · Yoshua Bengio · Jason Hartford

ARTree: A Deep Autoregressive Model for Phylogenetic Inference

Tianyu Xie · Cheng Zhang

BIOT: Biosignal Transformer for Cross-data Learning in the Wild

Chaoqi Yang · M Westover · Jimeng Sun

Towards Semi-Structured Automatic ICD Coding via Tree-based Contrastive Learning

Chang Lu · Chandan Reddy · Ping Wang · Yue Ning

Risk-Averse Active Sensing for Timely Outcome Prediction under Cost Pressure

Yuchao Qin · Mihaela van der Schaar · Changhee Lee

Spatio-Angular Convolutions for Super-resolution in Diffusion MRI

Matthew Lyon · Paul Armitage · Mauricio A Álvarez

SpecTr: Fast Speculative Decoding via Optimal Transport

Ziteng Sun · Ananda Theertha Suresh · Jae Hun Ro · Ahmad Beirami · Himanshu Jain · Felix Yu

SatLM: Satisfiability-Aided Language Models Using Declarative Prompting

Xi Ye · Qiaochu Chen · Isil Dillig · Greg Durrett

Can Language Models Solve Graph Problems in Natural Language?

Heng Wang · Shangbin Feng · Tianxing He · Zhaoxuan Tan · Xiaochuang Han · Yulia Tsvetkov

Localized Symbolic Knowledge Distillation for Visual Commonsense Models

Jae Sung Park · Jack Hessel · Khyathi Chandu · Paul Pu Liang · Ximing Lu · Peter West · Youngjae Yu · Qiuyuan Huang · Jianfeng Gao · Ali Farhadi · Yejin Choi

SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks

Bill Yuchen Lin · Yicheng Fu · Karina Yang · Faeze Brahman · Shiyu Huang · Chandra Bhagavatula · Prithviraj Ammanabrolu · Yejin Choi · Xiang Ren

Guiding Large Language Models via Directional Stimulus Prompting

Zekun Li · Baolin Peng · Pengcheng He · Michel Galley · Jianfeng Gao · Xifeng Yan

Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning

Xiaoming Shi · Siqiao Xue · Kangrui Wang · Fan Zhou · James Zhang · Jun Zhou · Chenhao Tan · Hongyuan Mei

UNSSOR: Unsupervised Neural Speech Separation by Leveraging Over-determined Training Mixtures

Zhong-Qiu Wang · Shinji Watanabe

Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Shunyu Yao · Dian Yu · Jeffrey Zhao · Izhak Shafran · Tom Griffiths · Yuan Cao · Karthik Narasimhan

EMMA-X: An EM-like Multilingual Pre-training Algorithm for Cross-lingual Representation Learning

Ping Guo · Xiangpeng Wei · Yue Hu · Baosong Yang · Dayiheng Liu · Fei Huang · jun xie

Language Models Meet World Models: Embodied Experiences Enhance Language Models

Jiannan Xiang · Tianhua Tao · Yi Gu · Tianmin Shu · Zirui Wang · Zichao Yang · Zhiting Hu

RECKONING: Reasoning through Dynamic Knowledge Encoding

Zeming Chen · Gail Weiss · Eric Mitchell · Asli Celikyilmaz · Antoine Bosselut

Paxion: Patching Action Knowledge in Video-Language Foundation Models

Zhenhailong Wang · Ansel Blume · Sha Li · Genglin Liu · Jaemin Cho · Zineng Tang · Mohit Bansal · Heng Ji

Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense

Kalpesh Krishna · Yixiao Song · Marzena Karpinska · John Wieting · Mohit Iyyer

MotionGPT: Human Motion as a Foreign Language

Biao Jiang · Xin Chen · Wen Liu · Jingyi Yu · Gang Yu · Tao Chen

Learning to Tokenize for Generative Retrieval

Weiwei Sun · Lingyong Yan · Zheng Chen · Shuaiqiang Wang · Haichao Zhu · Pengjie Ren · Zhumin Chen · Dawei Yin · Maarten Rijke · Zhaochun Ren

Inference-Time Intervention: Eliciting Truthful Answers from a Language Model

Kenneth Li · Oam Patel · Fernanda Viégas · Hanspeter Pfister · Martin Wattenberg

On-the-Fly Adapting Code Summarization on Trainable Cost-Effective Language Models

Yufan Cai · Yun Lin · Chenyan Liu · Jinglian Wu · Yifan Zhang · Yiming Liu · Yeyun Gong · Jin Song Dong

Repetition In Repetition Out: Towards Understanding Neural Text Degeneration from the Data Perspective

Huayang Li · Tian Lan · Zihao Fu · Deng Cai · Lemao Liu · Nigel Collier · Taro Watanabe · Yixuan Su

Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision

Jiaxin Zhang · Zhuohang Li · Kamalika Das · Sricharan Kumar

Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neural Networks without Weight Symmetry

Bariscan Bozkurt · Cengiz Pehlevan · Alper Erdogan

Low Tensor Rank Learning of Neural Dynamics

Arthur Pellegrino · N Alex Cayco Gajic · Angus Chadwick

Enhancing Adaptive History Reserving by Spiking Convolutional Block Attention Module in Recurrent Neural Networks

Qi Xu · Yuyuan Gao · Jiangrong Shen · Yaxin Li · Xuming Ran · Huajin Tang · Gang Pan

Cognitive Model Discovery via Disentangled RNNs

Kevin Miller · Maria Eckstein · Matt Botvinick · Zeb Kurth-Nelson

Explainable Brain Age Prediction using coVariance Neural Networks

Saurabh Sihag · Gonzalo Mateos · Corey McMillan · Alejandro Ribeiro

Temporal Conditioning Spiking Latent Variable Models of the Neural Response to Natural Visual Scenes

Gehua Ma · Runhao Jiang · Rui Yan · Huajin Tang

Performance-optimized deep neural networks are evolving into worse models of inferotemporal visual cortex

Drew Linsley · Ivan F Rodriguez Rodriguez · Thomas FEL · Michael Arcaro · Saloni Sharma · Margaret Livingstone · Thomas Serre

Contrast, Attend and Diffuse to Decode High-Resolution Images from Brain Activities

Jingyuan Sun · Mingxiao Li · Zijiao Chen · Yunhao Zhang · Shaonan Wang · Marie-Francine Moens

Expressive probabilistic sampling in recurrent neural networks

Shirui Chen · Linxing Jiang · Rajesh PN Rao · Eric Shea-Brown

Brain encoding models based on multimodal transformers can transfer across language and vision

Jerry Tang · Meng Du · Vy Vo · VASUDEV LAL · Alexander Huth

Separable Physics-Informed Neural Networks

Junwoo Cho · Seungtae Nam · Hyunmo Yang · Seok-Bae Yun · Youngjoon Hong · Eunbyung Park

SyncTREE: Fast Timing Analysis for Integrated Circuit Design through a Physics-informed Tree-based Graph Neural Network

Yuting Hu · Jiajie Li · Florian Klemme · Gi-Joon Nam · Tengfei Ma · Hussam Amrouch · Jinjun Xiong

Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks

Woojin Cho · Kookjin Lee · Donsub Rim · Noseong Park

Conformal Prediction for Uncertainty-Aware Planning with Diffusion Dynamics Model

Jiankai Sun · Yiqi Jiang · Jianing Qiu · Parth Nobel · Mykel J Kochenderfer · Mac Schwager

Real-Time Motion Prediction via Heterogeneous Polyline Transformer with Relative Pose Encoding

Zhejun Zhang · Alexander Liniger · Christos Sakaridis · Fisher Yu · Luc V Gool

Asynchrony-Robust Collaborative Perception via Bird's Eye View Flow

Sizhe Wei · Yuxi Wei · Yue Hu · Yifan Lu · Yiqi Zhong · Siheng Chen · Ya Zhang

Learning Environment-Aware Affordance for 3D Articulated Object Manipulation under Occlusions

Ruihai Wu · Kai Cheng · Yan Zhao · Chuanruo Ning · Guanqi Zhan · Hao Dong

Time Series as Images: Vision Transformer for Irregularly Sampled Time Series

Zekun Li · Shiyang Li · Xifeng Yan

Drift doesn't Matter: Dynamic Decomposition with Diffusion Reconstruction for Unstable Multivariate Time Series Anomaly Detection

Chengsen Wang · Zirui Zhuang · Qi Qi · Jingyu Wang · Xingyu Wang · Haifeng Sun · Jianxin Liao

Back-Modality: Leveraging Modal Transformation for Data Augmentation

Zhi Li · Yifan Liu · Yin Zhang

Sparse Parameterization for Epitomic Dataset Distillation

Xing Wei · Anjia Cao · Funing Yang · Zhiheng Ma

Collaborative Learning via Prediction Consensus

Dongyang Fan · Celestine Mendler-Dünner · Martin Jaggi

Train Faster, Perform Better: Modular Adaptive Training in Over-Parameterized Models

Yubin Shi · Yixuan Chen · Mingzhi Dong · Xiaochen Yang · Dongsheng Li · Yujiang Wang · Robert Dick · Qin Lv · Yingying Zhao · Fan Yang · Tun Lu · Ning Gu · Li Shang

NeuroGF: A Neural Representation for Fast Geodesic Distance and Path Queries

Qijian Zhang · Junhui Hou · Yohanes Adikusuma · Wenping Wang · Ying He

The geometry of hidden representations of large transformer models

Lucrezia Valeriani · Diego Doimo · Francesca Cuturello · Alessandro Laio · Alessio Ansuini · Alberto Cazzaniga

VCC: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens

Zhanpeng Zeng · Cole Hawkins · Mingyi Hong · Aston Zhang · Nikolaos Pappas · Vikas Singh · Shuai Zheng

TART: A plug-and-play Transformer module for task-agnostic reasoning

Kush Bhatia · Avanika Narayan · Christopher De Sa · Christopher Ré

Sparse Modular Activation for Efficient Sequence Modeling

Liliang Ren · Yang Liu · Shuohang Wang · Yichong Xu · Chenguang Zhu · Cheng Xiang Zhai

Distributed Inference and Fine-tuning of Large Language Models Over The Internet

Alexander Borzunov · Max Ryabinin · Artem Chumachenko · Dmitry Baranchuk · Tim Dettmers · Younes Belkada · Pavel Samygin · Colin Raffel

An Inductive Bias for Tabular Deep Learning

Ege Beyazit · Jonathan Kozaczuk · Bo Li · Vanessa Wallace · Bilal Fadlallah

Understanding Neural Network Binarization with Forward and Backward Proximal Quantizers

Yiwei Lu · Yaoliang Yu · Xinlin Li · Vahid Partovi Nia

MathNAS: If Blocks Have a Role in Mathematical Architecture Design

Qinsi Wang · Jinghan Ke · Zhi Liang · Sihai Zhang

ZipLM: Inference-Aware Structured Pruning of Language Models

Eldar Kurtić · Elias Frantar · Dan Alistarh · Dan Alistarh

Fine-Tuning Language Models with Just Forward Passes

Sadhika Malladi · Tianyu Gao · Eshaan Nichani · Alex Damian · Jason Lee · Danqi Chen · Sanjeev Arora

Learning Layer-wise Equivariances Automatically using Gradients

Tycho van der Ouderaa · Alexander Immer · Mark van der Wilk

Reusing Pretrained Models by Multi-linear Operators for Efficient Training

Yu Pan · Ye Yuan · Yichun Yin · Zenglin Xu · Lifeng Shang · Xin Jiang · Qun Liu

Enhancing Sharpness-Aware Optimization Through Variance Suppression

Bingcong Li · Georgios Giannakis

BayesTune: Bayesian Sparse Deep Model Fine-tuning

Minyoung Kim · Timothy Hospedales

NCDL: A Framework for Deep Learning on non-Cartesian Lattices

Joshua Horacsek · Usman Alim

CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra

Andres Potapczynski · Marc Finzi · Geoff Pleiss · Geoff Pleiss · Andrew Wilson

Bypass Exponential Time Preprocessing: Fast Neural Network Training via Weight-Data Correlation Preprocessing

Josh Alman · 杰昊梁 · Zhao Song · Ruizhe Zhang · Danyang Zhuo

Model-enhanced Vector Index

Hailin Zhang · Yujing Wang · Qi Chen · Ruiheng Chang · Ting Zhang · Ziming Miao · Yingyan Hou · Yang Ding · Xupeng Miao · Haonan Wang · Bochen Pang · Yuefeng Zhan · Hao Sun · Weiwei Deng · Qi Zhang · Fan Yang · Xing Xie · Mao Yang · Bin CUI

Max-Margin Token Selection in Attention Mechanism

Davoud Ataee Tarzanagh · Yingcong Li · Xuechen Zhang · Samet Oymak

The emergence of clusters in self-attention dynamics

Borjan Geshkovski · Cyril Letrouit · Yury Polyanskiy · Philippe Rigollet

On Separate Normalization in Self-supervised Transformers

Xiaohui Chen · Yinkai Wang · Yuanqi Du · Soha Hassoun · Liping Liu

Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection

Yu Bai · Fan Chen · Huan Wang · Caiming Xiong · Song Mei

Fast Attention Over Long Sequences With Dynamic Sparse Flash Attention

Matteo Pagliardini · Daniele Paliotta · Martin Jaggi · François Fleuret

Exposing Attention Glitches with Flip-Flop Language Modeling

Bingbin Liu · Jordan Ash · Surbhi Goel · Akshay Krishnamurthy · Cyril Zhang

Encoding Human Behavior in Information Design through Deep Learning

Guanghui Yu · Wei Tang · Saumik Narayanan · Chien-Ju Ho

GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction

Rui Yang · Lin Song · Yanwei Li · Sijie Zhao · Yixiao Ge · Xiu Li · Ying Shan

Lie Point Symmetry and Physics-Informed Networks

Tara Akhound-Sadegh · Laurence Perreault-Levasseur · Johannes Brandstetter · Max Welling · Siamak Ravanbakhsh

Empowering Convolutional Neural Nets with MetaSin Activation

Farnood Salehi · Tunç Aydin · André Gaillard · Guglielmo Camporese · Yuxuan Wang

Multiplication-Free Transformer Training via Piecewise Affine Operations

Atli Kosson · Martin Jaggi

Learning to Reason and Memorize with Self-Notes

Jack Lanchantin · Shubham Toshniwal · Jason Weston · arthur szlam · Sainbayar Sukhbaatar

REx: Data-Free Residual Quantization Error Expansion

Edouard YVINEC · Arnaud Dapogny · Matthieu Cord · Kevin Bailly

Joint Training of Deep Ensembles Fails Due to Learner Collusion

Alan Jeffares · Tennison Liu · Jonathan Crabbé · Mihaela van der Schaar

A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference

Emile van Krieken · Thiviyan Thanapalasingam · Jakub Tomczak · Frank van Harmelen · Annette Ten Teije

Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models

Weijian Luo · Tianyang Hu · Shifeng Zhang · Jiacheng Sun · Zhenguo Li · Zhihua Zhang

Large Language Models of Code Fail at Completing Code with Potential Bugs

Tuan Dinh · Jinman Zhao · Jinman Zhao · Samson Tan · Renato Negrinho · Leonard Lausen · Sheng Zha · George Karypis

On Calibrating Diffusion Probabilistic Models

Tianyu Pang · Cheng Lu · Chao Du · Min Lin · Shuicheng Yan · Zhijie Deng

Is This Loss Informative? Faster Text-to-Image Customization by Tracking Objective Dynamics

Anton Voronov · Mikhail Khoroshikh · Artem Babenko · Max Ryabinin

Why think step by step? Reasoning emerges from the locality of experience

Ben Prystawski · Michael Li · Noah Goodman

Textually Pretrained Speech Language Models

Michael Hassid · Tal Remez · Tu Anh Nguyen · Itai Gat · Alexis CONNEAU · Felix Kreuk · Jade Copet · Alexandre Defossez · Gabriel Synnaeve · Emmanuel Dupoux · Roy Schwartz · Yossi Adi

Tree Variational Autoencoders

Laura Manduchi · Moritz Vandenhirtz · Alain Ryser · Julia Vogt

Towards Test-Time Refusals via Concept Negation

Peiran Dong · Song Guo · Junxiao Wang · Bingjie WANG · Jiewei Zhang · Ziming Liu

Counterfactual Generation with Identifiability Guarantees

Hanqi Yan · Lingjing Kong · Lin Gui · Yuejie Chi · Eric Xing · Yulan He · Kun Zhang

Contrastive Sampling Chains in Diffusion Models

Junyu Zhang · Daochang Liu · Shichao Zhang · Chang Xu

GLOBER: Coherent Non-autoregressive Video Generation via GLOBal Guided Video DecodER

Mingzhen Sun · Weining Wang · Zihan Qin · Jiahui Sun · Sihan Chen · Jing Liu

Likelihood-Based Diffusion Language Models

Ishaan Gulrajani · Tatsunori Hashimoto

From Discrete Tokens to High-Fidelity Audio Using Multi-Band Diffusion

Robin San Roman · Yossi Adi · Antoine Deleforge · Romain Serizel · Gabriel Synnaeve · Alexandre Defossez

SEEDS: Exponential SDE Solvers for Fast High-Quality Sampling from Diffusion Models

Martin Gonzalez · Nelson Fernandez Pinto · Thuy Tran · elies Gherbi · Hatem Hajri · Nader Masmoudi

Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Yuxin Wen · Neel Jain · John Kirchenbauer · Micah Goldblum · Jonas Geiping · Tom Goldstein

Diffusion Hyperfeatures: Searching Through Time and Space for Semantic Correspondence

Grace Luo · Lisa Dunlap · Dong Huk Park · Aleksander Holynski · Trevor Darrell

Conditional Score Guidance for Text-Driven Image-to-Image Translation

Hyunsoo Lee · Minsoo Kang · Bohyung Han

Regularizing Neural Networks with Meta-Learning Generative Models

Shin'ya Yamaguchi · Daiki Chijiwa · Sekitoshi Kanai · Atsutoshi Kumagai · Hisashi Kashima

Structured Neural Networks for Density Estimation and Causal Inference

Asic Chen · Ruian (Ian) Shi · Xiang Gao · Ricardo Baptista · Rahul Krishnan

Parallel Sampling of Diffusion Models

Andy Shih · Suneel Belkhale · Stefano Ermon · Dorsa Sadigh · Nima Anari

DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting

Salva Rühling Cachay · Bo Zhao · Hailey Joren · Rose Yu

Normalizing flow neural networks by JKO scheme

Chen Xu · Xiuyuan Cheng · Yao Xie

NICE: NoIse-modulated Consistency rEgularization for Data-Efficient GANs

Yao Ni · Piotr Koniusz

Mirror Diffusion Models for Constrained and Watermarked Generation

Guan-Horng Liu · Tianrong Chen · Evangelos Theodorou · Molei Tao

Context-guided Embedding Adaptation for Effective Topic Modeling in Low-Resource Regimes

Yishi Xu · Jianqiao Sun · Yudi Su · Xinyang Liu · Zhibin Duan · Bo Chen · Mingyuan Zhou

Autodecoding Latent 3D Diffusion Models

Evangelos Ntavelis · Aliaksandr Siarohin · Kyle Olszewski · Chaoyang Wang · Luc V Gool · Sergey Tulyakov

Towards Consistent Video Editing with Text-to-Image Diffusion Models

Zicheng Zhang · Bonan Li · Xuecheng Nie · Congying Han · Tiande Guo · Luoqi Liu

Exploring Diverse In-Context Configurations for Image Captioning

Xu Yang · Yongliang Wu · Mingzhuo Yang · Haokun Chen · Xin Geng

Distance-Restricted Folklore Weisfeiler-Leman GNNs with Provable Cycle Counting Power

Junru Zhou · Jiarui Feng · Xiyuan Wang · Muhan Zhang

Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization

Shurui Gui · Meng Liu · Xiner Li · Youzhi Luo · Shuiwang Ji

Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data

Xin Zheng · Miao Zhang · Chunyang Chen · Quoc Viet Hung Nguyen · Xingquan Zhu · Shirui Pan

Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts

Zeyang Zhang · Xin Wang · Ziwei Zhang · Zhou Qin · Weigao Wen · Hui Xue' · Haoyang Li · Wenwu Zhu

Simple and Asymmetric Graph Contrastive Learning without Augmentations

Teng Xiao · Huaisheng Zhu · Zhengyu Chen · Suhang Wang

Graph of Circuits with GNN for Exploring the Optimal Design Space

Aditya Shahane · Saripilli Swapna Manjiri · Ankesh Jain · Sandeep Kumar

Self-supervised Graph Neural Networks via Low-Rank Decomposition

Liang Yang · Runjie Shi · Qiuliang Zhang · bingxin niu · Zhen Wang · Xiaochun Cao · Chuan Wang

Unsupervised Graph Neural Architecture Search with Disentangled Self-Supervision

Zeyang Zhang · Xin Wang · Ziwei Zhang · Guangyao Shen · Shiqi Shen · Wenwu Zhu

Efficiently incorporating quintuple interactions into geometric deep learning force fields

Zun Wang · Guoqing Liu · Yichi Zhou · Tong Wang · Bin Shao

Towards Self-Interpretable Graph-Level Anomaly Detection

Yixin Liu · Kaize Ding · Qinghua Lu · Fuyi Li · Leo Yu Zhang · Shirui Pan

SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations

Qitian Wu · Wentao Zhao · Chenxiao Yang · Hengrui Zhang · Fan Nie · Haitian Jiang · Yatao Bian · Junchi Yan

Public Opinion Field Effect Fusion in Representation Learning for Trending Topics Diffusion

Junliang Li · Yang Yajun · Qinghua Hu · Xin Wang · Hong Gao

Learning Rule-Induced Subgraph Representations for Inductive Relation Prediction

Tianyu Liu · Qitan Lv · Jie Wang · Shuling Yang · Hanzhu Chen

Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman

Jiarui Feng · Lecheng Kong · Hao Liu · Dacheng Tao · Fuhai Li · Muhan Zhang · Yixin Chen

A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs

Zhaocheng Zhu · Xinyu Yuan · Michael Galkin · Louis-Pascal Xhonneux · Ming Zhang · Maxime Gazeau · Jian Tang

Does Graph Distillation See Like Vision Dataset Counterpart?

Beining Yang · Kai Wang · Qingyun Sun · Cheng Ji · Xingcheng Fu · Hao Tang · Yang You · Jianxin Li

Provable Training for Graph Contrastive Learning

Yue Yu · Xiao Wang · Mengmei Zhang · Nian Liu · Chuan Shi

Graph Convolutional Kernel Machine versus Graph Convolutional Networks

Zhihao Wu · Zhao Zhang · Jicong Fan

Probabilistic Invariant Learning with Randomized Linear Classifiers

Leonardo Cotta · Gal Yehuda · Assaf Schuster · Chris Maddison

An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations

Haoran Yang · Xiangyu Zhao · Yicong Li · Hongxu Chen · Guandong Xu

Multi-task Graph Neural Architecture Search with Task-aware Collaboration and Curriculum

Yijian Qin · Xin Wang · Ziwei Zhang · Hong Chen · Wenwu Zhu

Expressive Sign Equivariant Networks for Spectral Geometric Learning

Derek Lim · Joshua Robinson · Stefanie Jegelka · Haggai Maron

Category-Extensible Out-of-Distribution Detection via Hierarchical Context Descriptions

Kai Liu · Zhihang Fu · Chao Chen · Sheng Jin · Ze Chen · Mingyuan Tao · Rongxin Jiang · Jieping Ye

Accessing Higher Dimensions for Unsupervised Word Translation

Sida Wang

Test-Time Distribution Normalization for Contrastively Learned Visual-language Models

Yifei Zhou · Juntao Ren · Fengyu Li · Ramin Zabih · Ser Nam Lim

Feature Selection in the Contrastive Analysis Setting

Ethan Weinberger · Ian Covert · Su-In Lee

Learning-to-Rank Meets Language: Boosting Language-Driven Ordering Alignment for Ordinal Classification

Rui Wang · Peipei Li · Huaibo Huang · Chunshui Cao · Ran He · Zhaofeng He

LICO: Explainable Models with Language-Image COnsistency

Yiming Lei · Zilong Li · Yangyang Li · Junping Zhang · Hongming Shan

Efficient Equivariant Transfer Learning from Pretrained Models

Sourya Basu · Pulkit Katdare · Prasanna Sattigeri · Vijil Chenthamarakshan · Katherine Driggs-Campbell · Payel Das · Lav Varshney

Evaluating Neuron Interpretation Methods of NLP Models

Yimin Fan · Fahim Dalvi · Nadir Durrani · Hassan Sajjad

Riemannian Residual Neural Networks

Isay Katsman · Eric Chen · Sidhanth Holalkere · Anna Asch · Aaron Lou · Ser Nam Lim · Christopher De Sa

Deep Recurrent Optimal Stopping

Niranjan Damera Venkata · Chiranjib Bhattacharyya

Distributionally Robust Ensemble of Lottery Tickets Towards Calibrated Sparse Network Training

Hitesh Sapkota · Dingrong Wang · Zhiqiang Tao · Qi Yu

Adversarial Robustness through Random Weight Sampling

Yanxiang Ma · Minjing Dong · Chang Xu

Improving Adversarial Transferability via Intermediate-level Perturbation Decay

Qizhang Li · Yiwen Guo · Wangmeng Zuo · Hao Chen

Topological Parallax: A Geometric Specification for Deep Perception Models

Abraham Smith · Michael Catanzaro · Gabrielle Angeloro · Nirav Patel · Paul Bendich

Improving Robustness with Adaptive Weight Decay

Mohammad Amin Ghiasi · Ali Shafahi · Reza Ardekani

Which Models have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness

Suraj Srinivas · Sebastian Bordt · Himabindu Lakkaraju

RDumb: A simple approach that questions our progress in continual test-time adaptation

Ori Press · Steffen Schneider · Steffen Schneider · Matthias Kümmerer · Matthias Bethge

Characterizing Out-of-Distribution Error via Optimal Transport

Yuzhe Lu · Yilong Qin · Runtian Zhai · Andrew Shen · Ketong Chen · Zhenlin Wang · Soheil Kolouri · Simon Stepputtis · Joseph Campbell · Katia Sycara

Fast Trainable Projection for Robust Fine-tuning

Junjiao Tian · Yen-Cheng Liu · James S Smith · Zsolt Kira

Optimal Parameter and Neuron Pruning for Out-of-Distribution Detection

Chao Chen · Zhihang Fu · Kai Liu · Ze Chen · Mingyuan Tao · Jieping Ye

NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks

Seokil Ham · Jungwuk Park · Dong-Jun Han · Jaekyun Moon

Unlocking Deterministic Robustness Certification on ImageNet

Kai Hu · Andy Zou · Zifan Wang · Klas Leino · Matt Fredrikson

Towards Evaluating Transfer-based Attacks Systematically, Practically, and Fairly

Qizhang Li · Yiwen Guo · Wangmeng Zuo · Hao Chen

Batchnorm Allows Unsupervised Radial Attacks

Amur Ghose · Apurv Gupta · Yaoliang Yu · Pascal Poupart

TrojLLM: A Black-box Trojan Prompt Attack on Large Language Models

Jiaqi Xue · Mengxin Zheng · Ting Hua · Yilin Shen · Yepeng Liu · Ladislau Bölöni · Qian Lou

On the Role of Randomization in Adversarially Robust Classification

Lucas Gnecco Heredia · Muni Sreenivas Pydi · Laurent Meunier · Benjamin Negrevergne · Yann Chevaleyre

Enhancing Adversarial Robustness via Score-Based Optimization

Boya Zhang · Weijian Luo · Zhihua Zhang

RevColV2: Exploring Disentangled Representations in Masked Image Modeling

Qi Han · Yuxuan Cai · Yuxuan Cai · Xiangyu Zhang

Uncovering the Hidden Dynamics of Video Self-supervised Learning under Distribution Shifts

Pritam Sarkar · Ahmad Beirami · Ali Etemad

Relax, it doesn’t matter how you get there: A new self-supervised approach for multi-timescale behavior analysis

Mehdi Azabou · Michael Mendelson · Nauman Ahad · Maks Sorokin · Shantanu Thakoor · Carolina Urzay · Eva Dyer

Modality-Agnostic Self-Supervised Learning with Meta-Learned Masked Auto-Encoder

Huiwon Jang · Jihoon Tack · Daewon Choi · Jongheon Jeong · Jinwoo Shin

Keypoint-Augmented Self-Supervised Learning for Medical Image Segmentation with Limited Annotation

Zhangsihao Yang · Mengwei Ren · Kaize Ding · Guido Gerig · Yalin Wang

Deep Insights into Noisy Pseudo Labeling on Graph Data

Botao WANG · Jia Li · Yang Liu · Jiashun Cheng · Yu Rong · Wenjia Wang · Fugee Tsung

UP-DP: Unsupervised Prompt Learning for Data Pre-Selection with Vision-Language Models

Xin Li · Sima Behpour · Thang Long Doan · Wenbin He · Liang Gou · Liu Ren

Factorized Contrastive Learning: Going Beyond Multi-view Redundancy

Paul Pu Liang · Zihao Deng · Martin Q. Ma · James Zou · Louis-Philippe Morency · Ruslan Salakhutdinov

Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning

Berken Utku Demirel · Christian Holz

Block-State Transformers

Jonathan Pilault · Mahan Fathi · Orhan Firat · Chris Pal · Pierre-Luc Bacon · Ross Goroshin

Perceptual Kalman Filters: Online State Estimation under a Perfect Perceptual-Quality Constraint

Dror Freirich · Tomer Michaeli · Ron Meir

FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective

Kun Yi · Qi Zhang · Wei Fan · Hui He · Liang Hu · Pengyang Wang · Ning An · Longbing Cao · Zhendong Niu

Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models

Alex Damian · Eshaan Nichani · Rong Ge · Jason Lee

Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem

Tal Amir · Steven Gortler · Ilai Avni · Ravina Ravina · Nadav Dym

Functional Equivalence and Path Connectivity of Reducible Hyperbolic Tangent Networks

Matthew Farrugia-Roberts

Connecting Pre-trained Language Model and Downstream Task via Properties of Representation

Chenwei Wu · Holden Lee · Rong Ge

Does a sparse ReLU network training problem always admit an optimum ?

TUNG LE · QUOC-TUNG LE · Remi Gribonval · Elisa Riccietti

Training Neural Networks is NP-Hard in Fixed Dimension

Vincent Froese · Christoph Hertrich

Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck

Benjamin Edelman · Surbhi Goel · Sham Kakade · Eran Malach · Cyril Zhang

Path Regularization: A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks

Tolga Ergen · Mert Pilanci

Beyond NTK with Vanilla Gradient Descent: A Mean-Field Analysis of Neural Networks with Polynomial Width, Samples, and Time

Arvind Mahankali · Haochen Zhang · Kefan Dong · Margalit Glasgow · Tengyu Ma

Nearly Optimal VC-Dimension and Pseudo-Dimension Bounds for Deep Neural Network Derivatives

Yahong Yang · Haizhao Yang · Yang Xiang

Fixing the NTK: From Neural Network Linearizations to Exact Convex Programs

Rajat Vadiraj Dwaraknath · Tolga Ergen · Mert Pilanci

Trust Your $\nabla$: Gradient-based Intervention Targeting for Causal Discovery

Mateusz Olko · Michał Zając · Aleksandra Nowak · Nino Scherrer · Yashas Annadani · Stefan Bauer · Łukasz Kuciński · Piotr Miłoś

Causal Imitability Under Context-Specific Independence Relations

Fateme Jamshidi · Sina Akbari · Negar Kiyavash

Nonparametric Identifiability of Causal Representations from Unknown Interventions

Julius von Kügelgen · Michel Besserve · Liang Wendong · Luigi Gresele · Armin Kekić · Elias Bareinboim · David Blei · Bernhard Schölkopf

Learning Nonparametric Latent Causal Graphs with Unknown Interventions

Yibo Jiang · Bryon Aragam

Identification of Nonlinear Latent Hierarchical Models

Lingjing Kong · Biwei Huang · Feng Xie · Eric Xing · Yuejie Chi · Kun Zhang

Finding Counterfactually Optimal Action Sequences in Continuous State Spaces

Stratis Tsirtsis · Manuel Rodriguez

Double and Single Descent in Causal Inference with an Application to High-Dimensional Synthetic Control

Jann Spiess · guido imbens · Amar Venugopal

Causal Discovery in Semi-Stationary Time Series

Shanyun Gao · Raghavendra Addanki · Tong Yu · Ryan Rossi · Murat Kocaoglu

Data Augmentations for Improved (Large) Language Model Generalization

Amir Feder · Yoav Wald · Claudia Shi · Suchi Saria · David Blei

Generalizing Nonlinear ICA Beyond Structural Sparsity

Yujia Zheng · Kun Zhang

Rehearsal Learning for Avoiding Undesired Future

Tian Qin · Tian-Zuo Wang · Zhi-Hua Zhou

Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models

Litu Rout · Negin Raoof · Giannis Daras · Constantine Caramanis · Alex Dimakis · Sanjay Shakkottai

AdANNS: A Framework for Adaptive Semantic Search

Aniket Rege · Aditya Kusupati · Sharan Ranjit S · Alan Fan · Qingqing Cao · Sham Kakade · Prateek Jain · Ali Farhadi

Horospherical Decision Boundaries for Large Margin Classification in Hyperbolic Space

Xiran Fan · Chun-Hao Yang · Baba Vemuri

Sequential Predictive Two-Sample and Independence Testing

Aleksandr Podkopaev · Aaditya Ramdas

Gacs-Korner Common Information Variational Autoencoder

Michael Kleinman · Alessandro Achille · Stefano Soatto · Jonathan Kao

BanditPAM++: Faster $k$-medoids Clustering

Mo Tiwari · Ryan Kang · Donghyun Lee · Sebastian Thrun · Ilan Shomorony · Martin Zhang

Multinomial Logistic Regression: Asymptotic Normality on Null Covariates in High-Dimensions

Kai Tan · Pierre C Bellec

CosNet: A Generalized Spectral Kernel Network

Yanfang Xue · Pengfei Fang · Jinyue Tian · Shipeng Zhu · hui xue

On kernel-based statistical learning theory in the mean field limit

Christian Fiedler · Michael Herty · Sebastian Trimpe

An Efficient Doubly-Robust Test for the Kernel Treatment Effect

Diego Martinez Taboada · Aaditya Ramdas · Edward Kennedy

Maximum Average Randomly Sampled: A Scale Free and Non-parametric Algorithm for Stochastic Bandits

Masoud Moravej Khorasani · Erik Weyer

No-regret Algorithms for Fair Resource Allocation

Abhishek Sinha · Ativ Joshi · Rajarshi Bhattacharjee · Cameron Musco · Mohammad Hajiesmaili

Smoothed Online Learning for Prediction in Piecewise Affine Systems

Adam Block · Max Simchowitz · Russ Tedrake

Online Inventory Problems: Beyond the i.i.d. Setting with Online Convex Optimization

Massil HIHAT · Stéphane Gaïffas · Guillaume Garrigos · Simon Bussy

Anytime Model Selection in Linear Bandits

Parnian Kassraie · Nicolas Emmenegger · Andreas Krause · Aldo Pacchiano

Transportability for Bandits with Data from Different Environments

Alexis Bellot · Alan Malek · Silvia Chiappa

CS4ML: A general framework for active learning with arbitrary data based on Christoffel functions

Juan M. Cardenas · Ben Adcock · Nick Dexter

Adapting to Continuous Covariate Shift via Online Density Ratio Estimation

Yu-Jie Zhang · Zhen-Yu Zhang · Peng Zhao · Masashi Sugiyama

Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings

Sudhanshu Chanpuriya · Ryan Rossi · Anup B. Rao · Tung Mai · Nedim Lipka · Zhao Song · Cameron Musco

DAMEX: Dataset-aware Mixture-of-Experts for visual understanding of mixture-of-datasets

Yash Jain · Harkirat Behl · Zsolt Kira · Vibhav Vineet

Rank-N-Contrast: Learning Continuous Representations for Regression

Kaiwen Zha · Peng Cao · Jeany Son · Yuzhe Yang · Dina Katabi

A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning

Yiyou Sun · Zhenmei Shi · Yixuan Li

Temporally Disentangled Representation Learning under Unknown Nonstationarity

Xiangchen Song · Weiran Yao · Yewen Fan · Xinshuai Dong · Guangyi Chen · Juan Carlos Niebles · Eric Xing · Kun Zhang

Sequential Subset Matching for Dataset Distillation

JIAWEI DU · Qin Shi · Joey Tianyi Zhou

DeepPCR: Parallelizing Sequential Operations in Neural Networks

Federico Danieli · Miguel Sarabia · Xavier Suau Cuadros · Pau Rodriguez · Luca Zappella

Tight Bounds for Volumetric Spanners and Applications

Aditya Bhaskara · Sepideh Mahabadi · Ali Vakilian

On the Size and Approximation Error of Distilled Datasets

Alaa Maalouf · Murad Tukan · Noel Loo · Ramin Hasani · Mathias Lechner · Daniela Rus

Unbalanced Low-rank Optimal Transport Solvers

Meyer Scetbon · Michal Klein · Giovanni Palla · Marco Cuturi

Integration-free Training for Spatio-temporal Multimodal Covariate Deep Kernel Point Processes

YIXUAN ZHANG · Quyu Kong · Feng Zhou

Time Series Kernels based on Nonlinear Vector AutoRegressive Delay Embeddings

Giovanni De Felice · John Goulermas · Vladimir Gusev

Estimating Riemannian Metric with Noise-Contaminated Intrinsic Distance

Jiaming Qiu · Xiongtao Dai

Anchor Data Augmentation

Nora Schneider · Shirin Goshtasbpour · Fernando Perez-Cruz

A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning

Zitai Wang · Qianqian Xu · Zhiyong Yang · Yuan He · Xiaochun Cao · Qingming Huang

Meta-AdaM: An Meta-Learned Adaptive Optimizer with Momentum for Few-Shot Learning

Siyuan Sun · Hongyang Gao

Your representations are in the network: composable and parallel adaptation for large scale models

Yonatan Dukler · Alessandro Achille · Hao Yang · Varsha Vivek · Luca Zancato · Benjamin Bowman · Avinash Ravichandran · Charless Fowlkes · Ashwin Swaminathan · Stefano Soatto

The s-value: evaluating stability with respect to distributional shifts

Suyash Gupta · Dominik Rothenhäusler

4M: Massively Multimodal Masked Modeling

David Mizrahi · Roman Bachmann · Oguzhan Kar · Teresa Yeo · Teresa Yeo · Mingfei Gao · Afshin Dehghan · Amir Zamir

Parameter and Computation Efficient Transfer Learning for Vision-Language Pre-trained Models

Qiong Wu · Wei Yu · Yiyi Zhou · Shubin Huang · Xiaoshuai Sun · Rongrong Ji

Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classification

Tianjun Ke · Haoqun Cao · Zenan Ling · Feng Zhou

Efficient Adaptation of Large Vision Transformer via Adapter Re-Composing

Wei Dong · Dawei Yan · Zhijun Lin · Peng Wang

Federated Learning via Meta-Variational Dropout

Insu Jeon · Minui Hong · Junhyeog Yun · Gunhee Kim

RanPAC: Random Projections and Pre-trained Models for Continual Learning

Mark D. McDonnell · Dong Gong · Amin Parvaneh · Ehsan Abbasnejad · Anton van den Hengel

GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph

Xin Li · Dongze Lian · Zhihe Lu · Jiawang Bai · Zhibo Chen · Xinchao Wang

Meta-Learning with Neural Bandit Scheduler

Yunzhe Qi · Yikun Ban · Tianxin Wei · Jiaru Zou · Huaxiu Yao · Jingrui He

Fully Dynamic $k$-Clustering in $\tilde O(k)$ Update Time

Sayan Bhattacharya · Martín Costa · Silvio Lattanzi · Nikos Parotsidis

Promises and Pitfalls of Threshold-based Auto-labeling

Harit Vishwakarma · Heguang Lin · Frederic Sala · Ramya Korlakai Vinayak

Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning

Ming-Kun Xie · Jiahao Xiao · Hao-Zhe Liu · Gang Niu · Masashi Sugiyama · Sheng-Jun Huang

Beyond Myopia: Learning from Positive and Unlabeled Data through Holistic Predictive Trends

Wang Xinrui · Wenhai Wan · Chuanxing Geng · Shao-Yuan Li · Songcan Chen

Exact recovery and Bregman hard clustering of node-attributed Stochastic Block Model

Maximilien Dreveton · Felipe Fernandes · Daniel Figueiredo

Federated Spectral Clustering via Secure Similarity Reconstruction

Dong Qiao · Chris Ding · Jicong Fan

Characterizing the Impacts of Semi-supervised Learning for Weak Supervision

Jeffrey Li · Jieyu Zhang · Ludwig Schmidt · Alexander Ratner

Optimistic Meta-Gradients

Sebastian Flennerhag · Tom Zahavy · Brendan O'Donoghue · Hado van Hasselt · András György · Satinder Singh

Contextual Stochastic Bilevel Optimization

Yifan Hu · Jie Wang · Yao Xie · Andreas Krause · Daniel Kuhn

SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning

Yifan Yang · Peiyao Xiao · Kaiyi Ji

Making Scalable Meta Learning Practical

Sang Choe · Sanket Vaibhav Mehta · Sanket Vaibhav Mehta · Hwijeen Ahn · Willie Neiswanger · Pengtao Xie · Pengtao Xie · Emma Strubell · Eric Xing

Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs

Dongsheng Ding · Chen-Yu Wei · Kaiqing Zhang · Alejandro Ribeiro

Convergence analysis of ODE models for accelerated first-order methods via positive semidefinite kernels

Jungbin Kim · Insoon Yang

A Robust Exact Algorithm for the Euclidean Bipartite Matching Problem

Akshaykumar Gattani · Sharath Raghvendra · Pouyan Shirzadian

Bayesian Optimisation of Functions on Graphs

Xingchen Wan · Pierre Osselin · Henry Kenlay · Binxin Ru · Michael A Osborne · Xiaowen Dong

Variational Annealing on Graphs for Combinatorial Optimization

Sebastian Sanokowski · Wilhelm Berghammer · Sepp Hochreiter · Sebastian Lehner

Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spaces

Leonard Papenmeier · Luigi Nardi · Matthias Poloczek

Necessary and Sufficient Conditions for Optimal Decision Trees using Dynamic Programming

Jacobus van der Linden · Mathijs de Weerdt · Emir Demirović

DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization

Haoran Ye · Jiarui Wang · Zhiguang Cao · Helan Liang · Yong Li

Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems

Samuel Hurault · Ulugbek Kamilov · Arthur Leclaire · Nicolas Papadakis

Structured Semidefinite Programming for Recovering Structured Preconditioners

Arun Jambulapati · Jerry Li · Christopher Musco · Kirankumar Shiragur · Aaron Sidford · Kevin Tian

Local Convergence of Gradient Methods for Min-Max Games: Partial Curvature Generically Suffices

Guillaume Wang · Lénaïc Chizat

Bringing regularized optimal transport to lightspeed: a splitting method adapted for GPUs

Jacob Lindbäck · Zesen Wang · Mikael Johansson

Adaptive SGD with Polyak stepsize and Line-search: Robust Convergence and Variance Reduction

Xiaowen Jiang · Sebastian Stich

Revisiting Area Convexity: Faster Box-Simplex Games and Spectrahedral Generalizations

Arun Jambulapati · Kevin Tian

A Variational Perspective on High-Resolution ODEs

Hoomaan Maskan · Konstantinos Zygalakis · Alp Yurtsever

Correlation Aware Sparsified Mean Estimation Using Random Projection

Shuli Jiang · PRANAY SHARMA · Gauri Joshi

Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds

Michael Crawshaw · Yajie Bao · Mingrui Liu

Large-Scale Distributed Learning via Private On-Device LSH

Tahseen Rabbani · Marco Bornstein · Furong Huang

$\textbf{A}^2\textbf{CiD}^2$: Accelerating Asynchronous Communication in Decentralized Deep Learning

Adel Nabli · Eugene Belilovsky · Edouard Oyallon

Solving a Class of Non-Convex Minimax Optimization in Federated Learning

Xidong Wu · Jianhui Sun · Zhengmian Hu · Aidong Zhang · Heng Huang

Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model

Zirui Liu · Guanchu Wang · Shaochen (Henry) Zhong · Zhaozhuo Xu · Daochen Zha · Ruixiang (Ryan) Tang · Zhimeng (Stephen) Jiang · Kaixiong Zhou · Vipin Chaudhary · Shuai Xu · Xia Hu

Efficient Activation Function Optimization through Surrogate Modeling

Garrett Bingham · Risto Miikkulainen

Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization

Fu Luo · Xi Lin · Fei Liu · Qingfu Zhang · Zhenkun Wang

ReSync: Riemannian Subgradient-based Robust Rotation Synchronization

Huikang Liu · Xiao Li · Anthony Man-Cho So

A Single-Loop Accelerated Extra-Gradient Difference Algorithm with Improved Complexity Bounds for Constrained Minimax Optimization

Yuanyuan Liu · Fanhua Shang · Weixin An · Junhao Liu · Hongying Liu · Zhouchen Lin

Convergence of Alternating Gradient Descent for Matrix Factorization

Rachel Ward · Tamara Kolda

Aiming towards the minimizers: fast convergence of SGD for overparametrized problems

Chaoyue Liu · Dmitriy Drusvyatskiy · Misha Belkin · Damek Davis · Yian Ma

A Unified Framework for Rank-based Loss Minimization

Rufeng Xiao · Yuze Ge · Rujun Jiang · Yifan Yan

Projection-Free Methods for Solving Nonconvex-Concave Saddle Point Problems

Morteza Boroun · Erfan Yazdandoost Hamedani · Afrooz Jalilzadeh

Distributionally Robust Bayesian Optimization with $\varphi$-divergences

Hisham Husain · Vu Nguyen · Anton van den Hengel

Predict-then-Calibrate: A New Perspective of Robust Contextual LP

Chunlin Sun · Linyu Liu · Xiaocheng Li

Efficient Uncertainty Quantification and Reduction for Over-Parameterized Neural Networks

Ziyi Huang · Henry Lam · Haofeng Zhang

Fast Exact Leverage Score Sampling from Khatri-Rao Products with Applications to Tensor Decomposition

Vivek Bharadwaj · Osman Asif Malik · Riley Murray · Laura Grigori · Aydin Buluc · James Demmel

A Dynamical System View of Langevin-Based Non-Convex Sampling

Mohammad Reza Karimi Jaghargh · Ya-Ping Hsieh · Andreas Krause

Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient Descent

Kruno Lehman · Alain Durmus · Umut Simsekli

Batch Bayesian Optimization For Replicable Experimental Design

Zhongxiang Dai · Zhongxiang Dai · Quoc Phong Nguyen · Sebastian Tay · Daisuke Urano · Richalynn Leong · Bryan Kian Hsiang Low · Patrick Jaillet

Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies

Oscar Li · James Harrison · Jascha Sohl-Dickstein · Virginia Smith · Luke Metz

Quantum Bayesian Optimization

Zhongxiang Dai · Zhongxiang Dai · Gregory Kang Ruey Lau · Arun Verma · YAO SHU · Bryan Kian Hsiang Low · Patrick Jaillet

Riemannian Laplace approximations for Bayesian neural networks

Federico Bergamin · Pablo Moreno-Muñoz · Søren Hauberg · Georgios Arvanitidis

Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation

Richard Gao · Michael Deistler · Jakob H Macke

Neural Sampling in Hierarchical Exponential-family Energy-based Models

Xingsi Dong · Si Wu

Learning Robust Statistics for Simulation-based Inference under Model Misspecification

Daolang Huang · Ayush Bharti · Amauri Souza · Luigi Acerbi · Samuel Kaski

Effective Bayesian Heteroscedastic Regression with Deep Neural Networks

Alexander Immer · Emanuele Palumbo · Alexander Marx · Julia Vogt

Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds

Paul Rosa · Slava Borovitskiy · Alexander Terenin · Judith Rousseau

Leveraging Locality and Robustness to Achieve Massively Scalable Gaussian Process Regression

Robert Allison · Anthony Stephenson · Samuel F · Edward O Pyzer-Knapp

Implicit Manifold Gaussian Process Regression

Bernardo Fichera · Slava Borovitskiy · Andreas Krause · Aude G Billard

The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions

Jonathan Schmidt · Philipp Hennig · Jörg Nick · Filip Tronarp

Deep Gaussian Markov Random Fields for Graph-Structured Dynamical Systems

Fiona Lippert · Bart Kranstauber · Emiel van Loon · Patrick Forré

Entropy-based Training Methods for Scalable Neural Implicit Samplers

Weijian Luo · Boya Zhang · Zhihua Zhang

Stochastic Approximation Algorithms for Systems of Interacting Particles

Mohammad Reza Karimi Jaghargh · Ya-Ping Hsieh · Andreas Krause

Greedy Poisson Rejection Sampling

Gergely Flamich

A Bayesian Take on Gaussian Process Networks

Enrico Giudice · Jack Kuipers · Giusi Moffa

The Memory-Perturbation Equation: Understanding Model's Sensitivity to Data

Peter Nickl · Lu Xu · Dharmesh Tailor · Thomas Möllenhoff · Mohammad Emtiyaz Khan

On the Convergence of Black-Box Variational Inference

Kyurae Kim · Jisu Oh · Kaiwen Wu · Yian Ma · Jacob Gardner

A Heavy-Tailed Algebra for Probabilistic Programming

Feynman Liang · Liam Hodgkinson · Michael Mahoney

Implicit Variational Inference for High-Dimensional Posteriors

Anshuk Uppal · Kristoffer Stensbo-Smidt · Wouter Boomsma · Jes Frellsen

Latent SDEs on Homogeneous Spaces

Sebastian Zeng · Florian Graf · Roland Kwitt

Learning non-Markovian Decision-Making from State-only Sequences

Aoyang Qin · Feng Gao · Qing Li · Song-Chun Zhu · Sirui Xie

Natural Language Instruction-following with Task-related Language Development and Translation

Jing-Cheng Pang · Xin-Yu Yang · Si-Hang Yang · Xiong-Hui Chen · Yang Yu

Learning Dynamic Attribute-factored World Models for Efficient Multi-object Reinforcement Learning

Fan Feng · Sara Magliacane

Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management

Dhawal Gupta · Yinlam Chow · Azamat Tulepbergenov · Mohammad Ghavamzadeh · Craig Boutilier

BEDD: The MineRL BASALT Evaluation and Demonstrations Dataset for Training and Benchmarking Agents that Solve Fuzzy Tasks

Stephanie Milani · Anssi Kanervisto · Karolis Ramanauskas · Sander Schulhoff · Brandon Houghton · Rohin Shah

MoVie: Visual Model-Based Policy Adaptation for View Generalization

Sizhe Yang · Yanjie Ze · Yanjie Ze · Huazhe Xu

Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation

Nikki Lijing Kuang · Ming Yin · Mengdi Wang · Yu-Xiang Wang · Yian Ma

Learning to Modulate pre-trained Models in RL

Thomas Schmied · Markus Hofmarcher · Fabian Paischer · Razvan Pascanu · Sepp Hochreiter

Spectral Entry-wise Matrix Estimation for Low-Rank Reinforcement Learning

Stefan Stojanovic · Yassir Jedra · Yassir Jedra · Alexandre Proutiere

A Definition of Continual Reinforcement Learning

David Abel · Andre Barreto · Benjamin Van Roy · Doina Precup · Hado van Hasselt · Satinder Singh

Inverse Reinforcement Learning with the Average Reward Criterion

Feiyang Wu · Jingyang Ke · Anqi Wu

HIQL: Offline Goal-Conditioned RL with Latent States as Actions

Seohong Park · Dibya Ghosh · Benjamin Eysenbach · Sergey Levine

Counterfactual-Augmented Importance Sampling for Semi-Offline Policy Evaluation

Shengpu Tang · Jenna Wiens

Elastic Decision Transformer

Yueh-Hua Wu · Xiaolong Wang · Masashi Hamaya

Context Shift Reduction for Offline Meta-Reinforcement Learning

Yunkai Gao · Rui Zhang · Jiaming Guo · Fan Wu · Qi Yi · Shaohui Peng · Siming Lan · Ruizhi Chen · Zidong Du · Xing Hu · Qi Guo · Ling Li · Yunji Chen

STEVE-1: A Generative Model for Text-to-Behavior in Minecraft

Shalev Lifshitz · Keiran Paster · Harris Chan · Jimmy Ba · Sheila McIlraith

Constrained Policy Optimization with Explicit Behavior Density For Offline Reinforcement Learning

Jing Zhang · Chi Zhang · Wenjia Wang · Bingyi Jing

Regularized Behavior Cloning for Blocking the Leakage of Past Action Information

Seokin Seo · HyeongJoo Hwang · Hongseok Yang · Kee-Eung Kim

Sample-Efficient and Safe Deep Reinforcement Learning via Reset Deep Ensemble Agents

Woojun Kim · Yongjae Shin · Jongeui Park · Youngchul Sung

Thought Cloning: Learning to Think while Acting by Imitating Human Thinking

Shengran Hu · Jeff Clune

PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning

Hojoon Lee · Hanseul Cho · HYUNSEUNG KIM · DAEHOON GWAK · Joonkee Kim · Jaegul Choo · Se-Young Yun · Chulhee Yun

A Unified Algorithm Framework for Unsupervised Discovery of Skills based on Determinantal Point Process

Jiayu Chen · Vaneet Aggarwal · Tian Lan

Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive Learning

Seungyong Moon · Junyoung Yeom · Bumsoo Park · Hyun Oh Song

STORM: Efficient Stochastic Transformer based World Models for Reinforcement Learning

Weipu Zhang · Gang Wang · Jian Sun · Yetian Yuan · Gao Huang

Cross-Episodic Curriculum for Transformer Agents

Lucy Xiaoyang Shi · Yunfan Jiang · Jake Grigsby · Linxi Fan · Yuke Zhu

Large Language Models Are Semi-Parametric Reinforcement Learning Agents

Danyang Zhang · Lu Chen · Situo Zhang · Hongshen Xu · Zihan Zhao · Kai Yu

Compositional Foundation Models for Hierarchical Planning

Anurag Ajay · Seungwook Han · Yilun Du · Shuang Li · Abhi Gupta · Tommi Jaakkola · Josh Tenenbaum · Leslie Kaelbling · Akash Srivastava · Pulkit Agrawal

Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models

Xingyuan Zhang · Philip Becker-Ehmck · Patrick van der Smagt · Maximilian Karl

Double Gumbel Q-Learning

David Yu-Tung Hui · Aaron Courville · Pierre-Luc Bacon

TD Convergence: An Optimization Perspective

Kavosh Asadi · Shoham Sabach · Yao Liu · Yao Liu · Omer Gottesman · Rasool Fakoor

Mixed-Initiative Multiagent Apprenticeship Learning for Human Training of Robot Teams

Esmaeil Seraj · Jerry Xiong · Mariah Schrum · Matthew Gombolay

Decompose a Task into Generalizable Subtasks in Multi-Agent Reinforcement Learning

Zikang Tian · Ruizhi Chen · Xing Hu · Ling Li · Rui Zhang · Fan Wu · Shaohui Peng · Jiaming Guo · Zidong Du · Qi Guo · Yunji Chen

Multi-Agent First Order Constrained Optimization in Policy Space

Youpeng Zhao · Yaodong Yang · Zhenbo Lu · Wengang Zhou · Houqiang Li

On Imitation in Mean-field Games

Giorgia Ramponi · Pavel Kolev · Olivier Pietquin · Niao He · Mathieu Lauriere · Matthieu Geist

Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback

Canzhe Zhao · Ruofeng Yang · Baoxiang Wang · Xuezhou Zhang · Shuai Li

Hybrid Search for Efficient Planning with Completeness Guarantees

Kalle Kujanpää · Joni Pajarinen · Alexander Ilin

Autonomous Capability Assessment of Sequential Decision-Making Systems in Stochastic Settings

Pulkit Verma · Rushang Karia · Siddharth Srivastava

Large Language Models as Commonsense Knowledge for Large-Scale Task Planning

Zirui Zhao · Wee Sun Lee · David Hsu

EDGI: Equivariant Diffusion for Planning with Embodied Agents

Johann Brehmer · Joey Bose · Pim de Haan · Taco Cohen

Evaluating Cognitive Maps and Planning in Large Language Models with CogEval

Ida Momennejad · Hosein Hasanbeig · Felipe Vieira Frujeri · Hiteshi Sharma · Nebojsa Jojic · Hamid Palangi · Robert Ness · Jonathan Larson

GraphMP: Graph Neural Network-based Motion Planning with Efficient Graph Search

Xiao Zang · Miao Yin · Jinqi Xiao · Saman Zonouz · Bo Yuan

Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees

Đorđe Žikelić · Đorđe Žikelić · Mathias Lechner · Abhinav Verma · Krishnendu Chatterjee · Thomas Henzinger

Safe Exploration in Reinforcement Learning: A Generalized Formulation and Algorithms

Akifumi Wachi · Wataru Hashimoto · Xun Shen · Kazumune Hashimoto

Mass-Producing Failures of Multimodal Systems with Language Models

Shengbang Tong · Erik Jones · Jacob Steinhardt

A Bayesian Approach To Analysing Training Data Attribution In Deep Learning

Elisa Nguyen · Minjoon Seo · Seong Joon Oh

The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance

Jon Donnelly · Srikar Katta · Cynthia Rudin · Edward Browne

On the Robustness of Removal-Based Feature Attributions

Chris Lin · Ian Covert · Su-In Lee

Concept Distillation: Leveraging Human-Centered Explanations for Model Improvement

Avani Gupta · Saurabh Saini · P J Narayanan

Explain Any Concept: Segment Anything Meets Concept-Based Explanation

Ao Sun · Pingchuan Ma · Yuanyuan Yuan · Shuai Wang

LEACE: Perfect linear concept erasure in closed form

Nora Belrose · David Schneider-Joseph · Shauli Ravfogel · Ryan Cotterell · Edward Raff · Stella Biderman

Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting

Miles Turpin · Julian Michael · Ethan Perez · Samuel Bowman

This Looks Like Those: Illuminating Prototypical Concepts Using Multiple Visualizations

Chiyu Ma · Brandon Zhao · Chaofan Chen · Cynthia Rudin

Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning

Amit Dhurandhar · Karthikeyan Natesan Ramamurthy · Kartik Ahuja · Vijay Arya

Auditing for Human Expertise

Rohan Alur · Loren Laine · Darrick Li · Manish Raghavan · Devavrat Shah · Dennis Shung

Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions

Hao Wang · Luxi He · Rui Gao · Flavio Calmon

Fair Canonical Correlation Analysis

Zhuoping Zhou · Davoud Ataee Tarzanagh · Bojian Hou · Boning Tong · Jia Xu · Yanbo Feng · Qi Long · Li Shen

Estimating and Controlling for Equalized Odds via Sensitive Attribute Predictors

Beepul Bharti · Paul Yi · Jeremias Sulam

Cookie Consent Has Disparate Impact on Estimation Accuracy

Erik Miehling · Rahul Nair · Elizabeth Daly · Karthikeyan Natesan Ramamurthy · Robert Redmond

Group Fairness in Peer Review

Haris Aziz · Evi Micha · Nisarg Shah

On Measuring Fairness in Generative Models

Christopher Teo · Milad Abdollahzadeh · Ngai-Man (Man) Cheung

Incentives in Private Collaborative Machine Learning

Rachael Sim · Yehong Zhang · Nghia Hoang · Xinyi Xu · Bryan Kian Hsiang Low · Patrick Jaillet

Strategic Behavior in Two-sided Matching Markets with Prediction-enhanced Preference-formation

Stefania Ionescu · Yuhao Du · Kenneth Joseph · Ancsa Hannak

WCLD: Curated Large Dataset of Criminal Cases from Wisconsin Circuit Courts

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Experiment Planning with Function Approximation

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Nonparametric Boundary Geometry in Physics Informed Deep Learning

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Online Control for Meta-optimization

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Fair, Polylog-Approximate Low-Cost Hierarchical Clustering

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LOVM: Language-Only Vision Model Selection

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