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Oral
Tue Dec 07 12:00 AM -- 12:15 AM (PST)
MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers
In Oral Session 1: Deep Learning
Krishna Pillutla · Swabha Swayamdipta · Rowan Zellers · John Thickstun · Sean Welleck · Yejin Choi · Zaid Harchaoui
Oral
Tue Dec 07 12:00 AM -- 12:15 AM (PST)
Framing RNN as a kernel method: A neural ODE approach
In Oral Session 1: Deep Learning Theory and Causality
Adeline Fermanian · Pierre Marion · Jean-Philippe Vert · Gérard Biau
Oral
Tue Dec 07 12:00 AM -- 12:15 AM (PST)
Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics
In Oral Session 1: Theory
Carles Domingo i Enrich · Youssef Mroueh
Oral
Tue Dec 07 12:00 AM -- 12:15 AM (PST)
E(n) Equivariant Normalizing Flows
In Oral Session 1: Generative Modeling
Victor Garcia Satorras · Emiel Hoogeboom · Fabian Fuchs · Ingmar Posner · Max Welling
Oral
Tue Dec 07 12:20 AM -- 12:35 AM (PST)
Learning to Draw: Emergent Communication through Sketching
In Oral Session 1: Deep Learning
Daniela Mihai · Jonathon Hare
Oral
Tue Dec 07 12:20 AM -- 12:35 AM (PST)
A Universal Law of Robustness via Isoperimetry
In Oral Session 1: Deep Learning Theory and Causality
Sebastien Bubeck · Mark Sellke
Oral
Tue Dec 07 12:20 AM -- 12:35 AM (PST)
Near-Optimal No-Regret Learning in General Games
In Oral Session 1: Theory
Constantinos Daskalakis · Maxwell Fishelson · Noah Golowich
Oral
Tue Dec 07 12:20 AM -- 12:35 AM (PST)
Online Variational Filtering and Parameter Learning
In Oral Session 1: Generative Modeling
Andrew Campbell · Yuyang Shi · Thomas Rainforth · Arnaud Doucet
Oral
Tue Dec 07 12:40 AM -- 12:55 AM (PST)
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions
In Oral Session 1: Theory
Yin Tat Lee · Ruoqi Shen · Kevin Tian
Oral
Tue Dec 07 12:40 AM -- 12:55 AM (PST)
Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons
In Oral Session 1: Deep Learning
Paul Haider · Benjamin Ellenberger · Laura Kriener · Jakob Jordan · Walter Senn · Mihai A. Petrovici
Oral
Tue Dec 07 12:40 AM -- 12:55 AM (PST)
Alias-Free Generative Adversarial Networks
In Oral Session 1: Generative Modeling
Tero Karras · Miika Aittala · Samuli Laine · Erik Härkönen · Janne Hellsten · Jaakko Lehtinen · Timo Aila
Oral
Tue Dec 07 12:40 AM -- 12:55 AM (PST)
Causal Identification with Matrix Equations
In Oral Session 1: Deep Learning Theory and Causality
Sanghack Lee · Elias Bareinboim
Oral
Tue Dec 07 01:00 AM -- 01:15 AM (PST)
EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback
In Oral Session 2: Optimization
Peter Richtarik · Igor Sokolov · Ilyas Fatkhullin
Oral
Tue Dec 07 01:00 AM -- 01:15 AM (PST)
Data driven semi-supervised learning
In Oral Session 2: Theory
Maria-Florina Balcan · Dravyansh Sharma
Oral
Tue Dec 07 01:00 AM -- 01:15 AM (PST)
Attention over Learned Object Embeddings Enables Complex Visual Reasoning
In Oral Session 2: Deep Learning
David Ding · Felix Hill · Adam Santoro · Malcolm Reynolds · Matt Botvinick
Oral
Tue Dec 07 01:00 AM -- 01:15 AM (PST)
An Exponential Lower Bound for Linearly Realizable MDP with Constant Suboptimality Gap
In Oral Session 2: Reinforcement Learning
Yuanhao Wang · Ruosong Wang · Sham Kakade
Oral
Tue Dec 07 01:20 AM -- 01:35 AM (PST)
Learning Frequency Domain Approximation for Binary Neural Networks
In Oral Session 2: Deep Learning
Yixing Xu · Kai Han · Chang Xu · Yehui Tang · Chunjing XU · Yunhe Wang
Oral
Tue Dec 07 01:20 AM -- 01:35 AM (PST)
Stability and Deviation Optimal Risk Bounds with Convergence Rate $O(1/n)$
In Oral Session 2: Theory
Yegor Klochkov · Nikita Zhivotovskiy
Oral
Tue Dec 07 01:20 AM -- 01:35 AM (PST)
Differentiable Quality Diversity
In Oral Session 2: Optimization
Matthew Fontaine · Stefanos Nikolaidis
Oral
Tue Dec 07 01:20 AM -- 01:35 AM (PST)
On the Expressivity of Markov Reward
In Oral Session 2: Reinforcement Learning
David Abel · Will Dabney · Anna Harutyunyan · Mark Ho · Michael Littman · Doina Precup · Satinder Singh
Oral
Tue Dec 07 01:40 AM -- 01:55 AM (PST)
The Complexity of Bayesian Network Learning: Revisiting the Superstructure
In Oral Session 2: Theory
Robert Ganian · Viktoriia Korchemna
Oral
Tue Dec 07 01:40 AM -- 01:55 AM (PST)
The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition
In Oral Session 2: Reinforcement Learning
Tiancheng Jin · Longbo Huang · Haipeng Luo
Oral
Tue Dec 07 01:40 AM -- 01:55 AM (PST)
Hessian Eigenspectra of More Realistic Nonlinear Models
In Oral Session 2: Optimization
Zhenyu Liao · Michael Mahoney
Oral
Tue Dec 07 01:40 AM -- 01:55 AM (PST)
Learning Debiased Representation via Disentangled Feature Augmentation
In Oral Session 2: Deep Learning
Jungsoo Lee · Eungyeup Kim · Juyoung Lee · Jihyeon Lee · Jaegul Choo
Oral
Wed Dec 08 08:00 AM -- 08:15 AM (PST)
Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms
In Oral Session 3: Optimization
Mathieu Even · Raphaël Berthier · Francis Bach · Nicolas Flammarion · Hadrien Hendrikx · Pierre Gaillard · Laurent Massoulié · Adrien Taylor
Oral
Wed Dec 08 08:00 AM -- 08:15 AM (PST)
Unsupervised Speech Recognition
In Oral Session 3: Deep Learning
Alexei Baevski · Wei-Ning Hsu · Alexis CONNEAU · Michael Auli
Oral
Wed Dec 08 08:00 AM -- 08:15 AM (PST)
Partial success in closing the gap between human and machine vision
In Oral Session 3: Vision Applications
Robert Geirhos · Kantharaju Narayanappa · Benjamin Mitzkus · Tizian Thieringer · Matthias Bethge · Felix A. Wichmann · Wieland Brendel
Oral
Wed Dec 08 08:00 AM -- 08:15 AM (PST)
Efficient First-Order Contextual Bandits: Prediction, Allocation, and Triangular Discrimination
In Oral Session 3: Theory
Dylan Foster · Akshay Krishnamurthy
Oral
Wed Dec 08 08:20 AM -- 08:35 AM (PST)
Bellman-consistent Pessimism for Offline Reinforcement Learning
In Oral Session 3: Theory
Tengyang Xie · Ching-An Cheng · Nan Jiang · Paul Mineiro · Alekh Agarwal
Oral
Wed Dec 08 08:20 AM -- 08:35 AM (PST)
Keeping Your Eye on the Ball: Trajectory Attention in Video Transformers
In Oral Session 3: Vision Applications
Mandela Patrick · Dylan Campbell · Yuki Asano · Ishan Misra · Florian Metze · Christoph Feichtenhofer · Andrea Vedaldi · João Henriques
Oral
Wed Dec 08 08:20 AM -- 08:35 AM (PST)
Deep Reinforcement Learning at the Edge of the Statistical Precipice
In Oral Session 3: Deep Learning
Rishabh Agarwal · Max Schwarzer · Pablo Samuel Castro · Aaron Courville · Marc Bellemare
Oral
Wed Dec 08 08:20 AM -- 08:35 AM (PST)
Oracle Complexity in Nonsmooth Nonconvex Optimization
In Oral Session 3: Optimization
Guy Kornowski · Ohad Shamir
Oral
Wed Dec 08 08:40 AM -- 08:55 AM (PST)
A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference
In Oral Session 3: Theory
Antonio Vergari · YooJung Choi · Anji Liu · Stefano Teso · Guy Van den Broeck
Oral
Wed Dec 08 08:40 AM -- 08:55 AM (PST)
Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss
In Oral Session 3: Deep Learning
Jeff Z. HaoChen · Colin Wei · Adrien Gaidon · Tengyu Ma
Oral
Wed Dec 08 08:40 AM -- 08:55 AM (PST)
Volume Rendering of Neural Implicit Surfaces
In Oral Session 3: Vision Applications
Lior Yariv · Jiatao Gu · Yoni Kasten · Yaron Lipman
Oral
Wed Dec 08 08:40 AM -- 08:55 AM (PST)
Faster Matchings via Learned Duals
In Oral Session 3: Optimization
Michael Dinitz · Sungjin Im · Thomas Lavastida · Benjamin Moseley · Sergei Vassilvitskii
Oral
Fri Dec 10 12:00 AM -- 12:15 AM (PST)
Passive attention in artificial neural networks predicts human visual selectivity
In Oral Session 4: Vision Applications and Optimization
Thomas Langlois · Haicheng Zhao · Erin Grant · Ishita Dasgupta · Tom Griffiths · Nori Jacoby
Oral
Fri Dec 10 12:00 AM -- 12:15 AM (PST)
Risk Monotonicity in Statistical Learning
In Oral Session 4: Theory
Zakaria Mhammedi
Oral
Fri Dec 10 12:20 AM -- 12:35 AM (PST)
Shape As Points: A Differentiable Poisson Solver
In Oral Session 4: Vision Applications and Optimization
Songyou Peng · Chiyu Jiang · Yiyi Liao · Michael Niemeyer · Marc Pollefeys · Andreas Geiger
Oral
Fri Dec 10 12:20 AM -- 12:35 AM (PST)
Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds and Benign Overfitting
In Oral Session 4: Theory
Frederic Koehler · Lijia Zhou · Danica J. Sutherland · Nathan Srebro
Oral
Fri Dec 10 12:40 AM -- 12:55 AM (PST)
Optimal Rates for Random Order Online Optimization
In Oral Session 4: Vision Applications and Optimization
Uri Sherman · Tomer Koren · Yishay Mansour
Oral
Fri Dec 10 12:40 AM -- 12:55 AM (PST)
The decomposition of the higher-order homology embedding constructed from the $k$-Laplacian
In Oral Session 4: Theory
Yu-Chia Chen · Marina Meila
Oral
Fri Dec 10 04:00 PM -- 04:15 PM (PST)
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning
In Oral Session 5: Fairness and Privacy
Yangsibo Huang · Samyak Gupta · Zhao Song · Kai Li · Sanjeev Arora
Oral
Fri Dec 10 04:00 PM -- 04:15 PM (PST)
Moser Flow: Divergence-based Generative Modeling on Manifolds
In Oral Session 5: Generative Modeling
Noam Rozen · Aditya Grover · Maximilian Nickel · Yaron Lipman
Oral
Fri Dec 10 04:00 PM -- 04:15 PM (PST)
MERLOT: Multimodal Neural Script Knowledge Models
In Oral Session 5: Optimization and Vision Applications
Rowan Zellers · Ximing Lu · Jack Hessel · Youngjae Yu · Jae Sung Park · Jize Cao · Ali Farhadi · Yejin Choi
Oral
Fri Dec 10 04:00 PM -- 04:15 PM (PST)
Interesting Object, Curious Agent: Learning Task-Agnostic Exploration
In Oral Session 5: Reinforcement Learning and Planning
Simone Parisi · Victoria Dean · Deepak Pathak · Abhinav Gupta
Oral
Fri Dec 10 04:00 PM -- 04:15 PM (PST)
DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras
In Oral Session 5: Vision Applications
Zachary Teed · Jia Deng
Oral
Fri Dec 10 04:20 PM -- 04:35 PM (PST)
Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification
In Oral Session 5: Reinforcement Learning and Planning
Ben Eysenbach · Sergey Levine · Russ Salakhutdinov
Oral
Fri Dec 10 04:20 PM -- 04:35 PM (PST)
Retiring Adult: New Datasets for Fair Machine Learning
In Oral Session 5: Fairness and Privacy
Frances Ding · Moritz Hardt · John Miller · Ludwig Schmidt
Oral
Fri Dec 10 04:20 PM -- 04:35 PM (PST)
High-probability Bounds for Non-Convex Stochastic Optimization with Heavy Tails
In Oral Session 5: Optimization and Vision Applications
Ashok Cutkosky · Harsh Mehta
Oral
Fri Dec 10 04:20 PM -- 04:35 PM (PST)
Learning with Noisy Correspondence for Cross-modal Matching
In Oral Session 5: Vision Applications
Zhenyu Huang · Guocheng Niu · Xiao Liu · Wenbiao Ding · Xinyan Xiao · Hua Wu · Xi Peng
Oral
Fri Dec 10 04:20 PM -- 04:35 PM (PST)
Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity
In Oral Session 5: Generative Modeling
Ran Liu · Mehdi Azabou · Max Dabagia · Chi-Heng Lin · Mohammad Gheshlaghi Azar · Keith Hengen · Michal Valko · Eva Dyer
Oral
Fri Dec 10 04:40 PM -- 04:55 PM (PST)
Adaptive Conformal Inference Under Distribution Shift
In Oral Session 5: Optimization and Vision Applications
Isaac Gibbs · Emmanuel Candes
Oral
Fri Dec 10 04:40 PM -- 04:55 PM (PST)
Sequential Causal Imitation Learning with Unobserved Confounders
In Oral Session 5: Reinforcement Learning and Planning
Daniel Kumor · Junzhe Zhang · Elias Bareinboim
Oral
Fri Dec 10 04:40 PM -- 04:55 PM (PST)
Learning Treatment Effects in Panels with General Intervention Patterns
In Oral Session 5: Generative Modeling
Vivek Farias · Andrew Li · Tianyi Peng