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- [ 64809 ] Active Bayesian Causal Inference
- [ 64810 ] Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis
- [ 64811 ] Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders
- [ 64812 ] Provable Benefit of Multitask Representation Learning in Reinforcement Learning
- [ 64813 ] Self-Supervised Learning via Maximum Entropy Coding
- [ 64816 ] Counterfactual Temporal Point Processes
- [ 64817 ] Provable Subspace Identification Under Post-Nonlinear Mixtures
- [ 64818 ] VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely?
- [ 64819 ] Learning Multi-resolution Functional Maps with Spectral Attention for Robust Shape Matching
Q&A on RocketChat immediately following Lightning Talks
Author Information
Kimia Noorbakhsh (Sharif University of Technology)
Ronan Perry (University of Washington)
Qi Lyu (Oregon State University)
Jiawei Jiang (Wuhan University)
Jiawei Jiang is a professor in School of Computer Science of Wuhan University. He obtained his Ph.D in Computer Science from Peking University in 2018. He worked as a postdoc researcher at ETH Zürich from 2019 to 2022. His research interests include, but are not limited to, machine learning systems, large-scale data analytics, graph processing, and federated learning. He has published more than 30 papers in top venues, e.g., SIGMOD, VLDB, ICDE, ICML, and NeurIPS.
Christian Toth (Graz University of Technology)
Olivier Jeunen (Amazon)
Olivier Jeunen is a Postdoctoral Scientist at Amazon. In 2021, received his PhD from the University of Antwerp with a thesis titled ``Offline Approaches to Recommendation with Online Success''. His research lies at the intersection of machine learning and information retrieval -- pursuing algorithmic advances from sound theoretical foundations. He has a track record of collaborating with prominent industrial research labs, and his recent work has been recognised with the ACM RecSys ’21 Best Student Paper Award.
Xin Liu (Department of Electronic Engineering, Tsinghua University)
Yuan Cheng (University of Science and Technology of China)
Lei Li (Ecole Polytechnique, France)
Manuel Rodriguez (Max Planck Institute for Software Systems)
Julius von Kügelgen (Max Planck Institute for Intelligent Systems Tübingen & University of Cambridge)
Lars Lorch (ETH Zürich)
Nicolas Donati (Ecole Polytechnique)
Lukas Burkhalter (ETH Zurich)
Xiao Fu (Oregon State University)
Zhongdao Wang (Huawei Technologies Ltd.)
Songtao Feng (Ohio State University, Columbus)
Ciarán Gilligan-Lee (Spotify & University College London)
I am a scientist based in London. My research focuses on causal inference and its applications. I am currently Head of the Causal Inference Research Lab at Spotify and an Honorary Associate Professor at University College London.
Rishabh Mehrotra (Spotify Research)
Fangcheng Fu (Peking University)
Jing Yang (Pennsylvania State University)
Bernhard Schölkopf (MPI for Intelligent Systems, Tübingen)
Bernhard Scholkopf received degrees in mathematics (London) and physics (Tubingen), and a doctorate in computer science from the Technical University Berlin. He has researched at AT&T Bell Labs, at GMD FIRST, Berlin, at the Australian National University, Canberra, and at Microsoft Research Cambridge (UK). In 2001, he was appointed scientific member of the Max Planck Society and director at the MPI for Biological Cybernetics; in 2010 he founded the Max Planck Institute for Intelligent Systems. For further information, see www.kyb.tuebingen.mpg.de/~bs.
Ya-Li Li (Tsinghua University)
Christian Knoll (Graz University of Technology)
Maks Ovsjanikov (Ecole polytechnique)
Andreas Krause (ETH Zurich)
Shengjin Wang (Tsinghua University, Tsinghua University)
Hong Zhang (University of Science and Technology of China)
Mounia Lalmas (Spotify)
Bolin Ding (Alibaba Group)
Bo Du (Wuhan University)
Yingbin Liang (The Ohio State University)
Franz Pernkopf (Signal Processing and Speech Communication Laboratory, Graz, Austria)
Robert Peharz (Graz University of Technology)
Anwar Hithnawi (ETHZ - ETH Zurich)
Julius von Kügelgen (Max Planck Institute for Intelligent Systems Tübingen & University of Cambridge)
Bo Li (UIUC)
Ce Zhang (ETH Zurich)
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2023 Poster: Non-Convex Bilevel Optimization with Time-Varying Objective Functions »
Sen Lin · Daouda Sow · Kaiyi Ji · Yingbin Liang · Ness Shroff -
2023 Poster: How to Turn Your Knowledge Graph Embeddings into Generative Models »
Lorenzo Loconte · Nicola Di Mauro · Robert Peharz · Antonio Vergari -
2023 Poster: WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data »
Maurice Weber · Carlo Siebenschuh · Rory Butler · Anton Alexandrov · Valdemar Thanner · Georgios Tsolakis · Haris Jabbar · Ian Foster · Bo Li · Rick Stevens · Ce Zhang -
2023 Poster: DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models »
Boxin Wang · Weixin Chen · Hengzhi Pei · Chulin Xie · Mintong Kang · Chenhui Zhang · Chejian Xu · Zidi Xiong · Ritik Dutta · Rylan Schaeffer · Sang Truong · Simran Arora · Mantas Mazeika · Dan Hendrycks · Zinan Lin · Yu Cheng · Sanmi Koyejo · Dawn Song · Bo Li -
2023 Poster: DataPerf: Benchmarks for Data-Centric AI Development »
Mark Mazumder · Colby Banbury · Xiaozhe Yao · Bojan Karlaš · William Gaviria Rojas · Sudnya Diamos · Greg Diamos · Lynn He · Alicia Parrish · Hannah Rose Kirk · Jessica Quaye · Charvi Rastogi · Douwe Kiela · David Jurado · David Kanter · Rafael Mosquera · Will Cukierski · Juan Ciro · Lora Aroyo · Bilge Acun · Lingjiao Chen · Mehul Raje · Max Bartolo · Evan Sabri Eyuboglu · Amirata Ghorbani · Emmett Goodman · Addison Howard · Oana Inel · Tariq Kane · Christine R. Kirkpatrick · D. Sculley · Tzu-Sheng Kuo · Jonas Mueller · Tristan Thrush · Joaquin Vanschoren · Margaret Warren · Adina Williams · Serena Yeung · Newsha Ardalani · Praveen Paritosh · Ce Zhang · James Zou · Carole-Jean Wu · Cody Coleman · Andrew Ng · Peter Mattson · Vijay Janapa Reddi -
2023 Oral: DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models »
Boxin Wang · Weixin Chen · Hengzhi Pei · Chulin Xie · Mintong Kang · Chenhui Zhang · Chejian Xu · Zidi Xiong · Ritik Dutta · Rylan Schaeffer · Sang Truong · Simran Arora · Mantas Mazeika · Dan Hendrycks · Zinan Lin · Yu Cheng · Sanmi Koyejo · Dawn Song · Bo Li -
2023 Oral: How to Turn Your Knowledge Graph Embeddings into Generative Models »
Lorenzo Loconte · Nicola Di Mauro · Robert Peharz · Antonio Vergari -
2023 : Deep Learning from Crowdsourced Labels with Identifiability Guarantees »
Shahana Ibrahim · Tri Nguyen · Xiao Fu -
2022 : Contributed Talk: DensePure: Understanding Diffusion Models towards Adversarial Robustness »
Zhongzhu Chen · Kun Jin · Jiongxiao Wang · Weili Nie · Mingyan Liu · Anima Anandkumar · Bo Li · Dawn Song -
2022 Workshop: Trustworthy and Socially Responsible Machine Learning »
Huan Zhang · Linyi Li · Chaowei Xiao · J. Zico Kolter · Anima Anandkumar · Bo Li -
2022 Workshop: Workshop on neuro Causal and Symbolic AI (nCSI) »
Matej Zečević · Devendra Dhami · Christina Winkler · Thomas Kipf · Robert Peharz · Petar Veličković -
2022 Spotlight: Fairness in Federated Learning via Core-Stability »
Bhaskar Ray Chaudhury · Linyi Li · Mintong Kang · Bo Li · Ruta Mehta -
2022 Competition: The Trojan Detection Challenge »
Mantas Mazeika · Dan Hendrycks · Huichen Li · Xiaojun Xu · Andy Zou · Sidney Hough · Arezoo Rajabi · Dawn Song · Radha Poovendran · Bo Li · David Forsyth -
2022 Spotlight: LOT: Layer-wise Orthogonal Training on Improving l2 Certified Robustness »
Xiaojun Xu · Linyi Li · Bo Li -
2022 Spotlight: Lightning Talks 5B-1 »
Devansh Arpit · Xiaojun Xu · Zifan Shi · Ivan Skorokhodov · Shayan Shekarforoush · Zhan Tong · Yiqun Wang · Shichong Peng · Linyi Li · Ivan Skorokhodov · Huan Wang · Yibing Song · David Lindell · Yinghao Xu · Seyed Alireza Moazenipourasil · Sergey Tulyakov · Peter Wonka · Yiqun Wang · Ke Li · David Fleet · Yujun Shen · Yingbo Zhou · Bo Li · Jue Wang · Peter Wonka · Marcus Brubaker · Caiming Xiong · Limin Wang · Deli Zhao · Qifeng Chen · Dit-Yan Yeung -
2022 Spotlight: Will Bilevel Optimizers Benefit from Loops »
Kaiyi Ji · Mingrui Liu · Yingbin Liang · Lei Ying -
2022 Spotlight: Lightning Talks 3B-2 »
Yu Huang · Tero Karras · Maxim Kodryan · Shiau Hong Lim · Shudong Huang · Ziyu Wang · Siqiao Xue · ILYAS MALIK · Ekaterina Lobacheva · Miika Aittala · Hongjie Wu · Yuhao Zhou · Yingbin Liang · Xiaoming Shi · Jun Zhu · Maksim Nakhodnov · Timo Aila · Yazhou Ren · James Zhang · Longbo Huang · Dmitry Vetrov · Ivor Tsang · Hongyuan Mei · Samuli Laine · Zenglin Xu · Wentao Feng · Jiancheng Lv -
2022 Spotlight: Provable Generalization of Overparameterized Meta-learning Trained with SGD »
Yu Huang · Yingbin Liang · Longbo Huang -
2022 Competition: Reconnaissance Blind Chess: An Unsolved Challenge for Multi-Agent Decision Making Under Uncertainty »
Ryan Gardner · Gino Perrotta · Corey Lowman · Casey Richardson · Andrew Newman · Jared Markowitz · Nathan Drenkow · Bart Paulhamus · Ashley J Llorens · Todd Neller · Raman Arora · Bo Li · Mykel J Kochenderfer -
2022 Spotlight: Certifying Some Distributional Fairness with Subpopulation Decomposition »
Mintong Kang · Linyi Li · Maurice Weber · Yang Liu · Ce Zhang · Bo Li -
2022 Spotlight: Lightning Talks 1A-4 »
Siwei Wang · Jing Liu · Nianqiao Ju · Shiqian Li · Eloïse Berthier · Muhammad Faaiz Taufiq · Arsene Fansi Tchango · Chen Liang · Chulin Xie · Jordan Awan · Jean-Francois Ton · Ziad Kobeissi · Wenguan Wang · Xinwang Liu · Kewen Wu · Rishab Goel · Jiaxu Miao · Suyuan Liu · Julien Martel · Ruobin Gong · Francis Bach · Chi Zhang · Rob Cornish · Sanmi Koyejo · Zhi Wen · Yee Whye Teh · Yi Yang · Jiaqi Jin · Bo Li · Yixin Zhu · Vinayak Rao · Wenxuan Tu · Gaetan Marceau Caron · Arnaud Doucet · Xinzhong Zhu · Joumana Ghosn · En Zhu -
2022 Spotlight: EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks »
Runlin Lei · Zhen Wang · Yaliang Li · Bolin Ding · Zhewei Wei -
2022 Spotlight: Active Bayesian Causal Inference »
Christian Toth · Lars Lorch · Christian Knoll · Andreas Krause · Franz Pernkopf · Robert Peharz · Julius von Kügelgen -
2022 Spotlight: Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis »
Ronan Perry · Julius von Kügelgen · Bernhard Schölkopf -
2022 Spotlight: Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders »
Olivier Jeunen · Ciarán Gilligan-Lee · Rishabh Mehrotra · Mounia Lalmas -
2022 Spotlight: Provable Benefit of Multitask Representation Learning in Reinforcement Learning »
Yuan Cheng · Songtao Feng · Jing Yang · Hong Zhang · Yingbin Liang -
2022 Spotlight: Self-Supervised Learning via Maximum Entropy Coding »
Xin Liu · Zhongdao Wang · Ya-Li Li · Shengjin Wang -
2022 Spotlight: Embrace the Gap: VAEs Perform Independent Mechanism Analysis »
Patrik Reizinger · Luigi Gresele · Jack Brady · Julius von Kügelgen · Dominik Zietlow · Bernhard Schölkopf · Georg Martius · Wieland Brendel · Michel Besserve -
2022 Spotlight: Counterfactual Temporal Point Processes »
Kimia Noorbakhsh · Manuel Rodriguez -
2022 Spotlight: Provable Subspace Identification Under Post-Nonlinear Mixtures »
Qi Lyu · Xiao Fu -
2022 Spotlight: VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely? »
Jiawei Jiang · Lukas Burkhalter · Fangcheng Fu · Bolin Ding · Bo Du · Anwar Hithnawi · Bo Li · Ce Zhang -
2022 Spotlight: Learning Multi-resolution Functional Maps with Spectral Attention for Robust Shape Matching »
Lei Li · Nicolas Donati · Maks Ovsjanikov -
2022 Spotlight: CoPur: Certifiably Robust Collaborative Inference via Feature Purification »
Jing Liu · Chulin Xie · Sanmi Koyejo · Bo Li -
2022 Spotlight: Lightning Talks 1B-1 »
Qitian Wu · Runlin Lei · Rongqin Chen · Luca Pinchetti · Yangze Zhou · Abhinav Kumar · Hans Hao-Hsun Hsu · Wentao Zhao · Chenhao Tan · Zhen Wang · Shenghui Zhang · Yuesong Shen · Tommaso Salvatori · Gitta Kutyniok · Zenan Li · Amit Sharma · Leong Hou U · Yordan Yordanov · Christian Tomani · Bruno Ribeiro · Yaliang Li · David P Wipf · Daniel Cremers · Bolin Ding · Beren Millidge · Ye Li · Yuhang Song · Junchi Yan · Zhewei Wei · Thomas Lukasiewicz -
2022 Competition: Real Robot Challenge III - Learning Dexterous Manipulation from Offline Data in the Real World »
Nico Gürtler · Georg Martius · Sebastian Blaes · Pavel Kolev · Cansu Sancaktar · Stefan Bauer · Manuel Wuethrich · Markus Wulfmeier · Martin Riedmiller · Arthur Allshire · Annika Buchholz · Bernhard Schölkopf -
2022 : Q & A »
Antonio Vergari · YooJung Choi · Robert Peharz -
2022 Tutorial: Probabilistic Circuits: Representations, Inference, Learning and Applications »
Antonio Vergari · YooJung Choi · Robert Peharz -
2022 : Tutorial part 1 »
Antonio Vergari · YooJung Choi · Robert Peharz -
2022 : Panel »
Pin-Yu Chen · Alex Gittens · Bo Li · Celia Cintas · Hilde Kuehne · Payel Das -
2022 : Homomorphism AutoEncoder --- Learning Group Structured Representations from Observed Transitions »
Hamza Keurti · Hsiao-Ru Pan · Michel Besserve · Benjamin F. Grewe · Bernhard Schölkopf -
2022 : Trustworthy Machine Learning in Autonomous Driving »
Bo Li -
2022 Workshop: Decentralization and Trustworthy Machine Learning in Web3: Methodologies, Platforms, and Applications »
Jian Lou · Zhiguang Wang · Chejian Xu · Bo Li · Dawn Song -
2022 : Invited Talk #5, Privacy-Preserving Data Synthesis for General Purposes, Bo Li »
Bo Li -
2022 : Fairness Panel »
Freedom Gumedze · Rachel Cummings · Bo Li · Robert Tillman · Edward Choi -
2022 : Panel Discussion »
Cheng Zhang · Mihaela van der Schaar · Ilya Shpitser · Aapo Hyvarinen · Yoshua Bengio · Bernhard Schölkopf -
2022 : Trustworthy Federated Learning »
Bo Li -
2022 Poster: Exploring the Latent Space of Autoencoders with Interventional Assays »
Felix Leeb · Stefan Bauer · Michel Besserve · Bernhard Schölkopf -
2022 Poster: Supervised Training of Conditional Monge Maps »
Charlotte Bunne · Andreas Krause · Marco Cuturi -
2022 Poster: Improving Certified Robustness via Statistical Learning with Logical Reasoning »
Zhuolin Yang · Zhikuan Zhao · Boxin Wang · Jiawei Zhang · Linyi Li · Hengzhi Pei · Bojan Karlaš · Ji Liu · Heng Guo · Ce Zhang · Bo Li -
2022 Poster: Provable Subspace Identification Under Post-Nonlinear Mixtures »
Qi Lyu · Xiao Fu -
2022 Poster: Near-Optimal Multi-Agent Learning for Safe Coverage Control »
Manish Prajapat · Matteo Turchetta · Melanie Zeilinger · Andreas Krause -
2022 Poster: Untargeted Backdoor Watermark: Towards Harmless and Stealthy Dataset Copyright Protection »
Yiming Li · Yang Bai · Yong Jiang · Yong Yang · Shu-Tao Xia · Bo Li -
2022 Poster: Fairness in Federated Learning via Core-Stability »
Bhaskar Ray Chaudhury · Linyi Li · Mintong Kang · Bo Li · Ruta Mehta -
2022 Poster: Amortized Inference for Causal Structure Learning »
Lars Lorch · Scott Sussex · Jonas Rothfuss · Andreas Krause · Bernhard Schölkopf -
2022 Poster: Neural Attentive Circuits »
Martin Weiss · Nasim Rahaman · Francesco Locatello · Chris Pal · Yoshua Bengio · Bernhard Schölkopf · Erran Li Li · Nicolas Ballas -
2022 Poster: Assaying Out-Of-Distribution Generalization in Transfer Learning »
Florian Wenzel · Andrea Dittadi · Peter Gehler · Carl-Johann Simon-Gabriel · Max Horn · Dominik Zietlow · David Kernert · Chris Russell · Thomas Brox · Bernt Schiele · Bernhard Schölkopf · Francesco Locatello -
2022 Poster: Movement Penalized Bayesian Optimization with Application to Wind Energy Systems »
Shyam Sundhar Ramesh · Pier Giuseppe Sessa · Andreas Krause · Ilija Bogunovic -
2022 Poster: Experimental Design for Linear Functionals in Reproducing Kernel Hilbert Spaces »
Mojmir Mutny · Andreas Krause -
2022 Poster: A Unifying Framework of Off-Policy General Value Function Evaluation »
Tengyu Xu · Zhuoran Yang · Zhaoran Wang · Yingbin Liang -
2022 Poster: Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning »
Wenhao Ding · Haohong Lin · Bo Li · DING ZHAO -
2022 Poster: Direct Advantage Estimation »
Hsiao-Ru Pan · Nico Gürtler · Alexander Neitz · Bernhard Schölkopf -
2022 Poster: Certifying Some Distributional Fairness with Subpopulation Decomposition »
Mintong Kang · Linyi Li · Maurice Weber · Yang Liu · Ce Zhang · Bo Li -
2022 Poster: Graph Neural Network Bandits »
Parnian Kassraie · Andreas Krause · Ilija Bogunovic -
2022 Poster: On the Convergence Theory for Hessian-Free Bilevel Algorithms »
Daouda Sow · Kaiyi Ji · Yingbin Liang -
2022 Poster: Probable Domain Generalization via Quantile Risk Minimization »
Cian Eastwood · Alexander Robey · Shashank Singh · Julius von Kügelgen · Hamed Hassani · George J. Pappas · Bernhard Schölkopf -
2022 Poster: Interventions, Where and How? Experimental Design for Causal Models at Scale »
Panagiotis Tigas · Yashas Annadani · Andrew Jesson · Bernhard Schölkopf · Yarin Gal · Stefan Bauer -
2022 Poster: Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis »
Ronan Perry · Julius von Kügelgen · Bernhard Schölkopf -
2022 Poster: Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization »
Aniket Das · Bernhard Schölkopf · Michael Muehlebach -
2022 Poster: NCP: Neural Correspondence Prior for Effective Unsupervised Shape Matching »
Souhaib Attaiki · Maks Ovsjanikov -
2022 Poster: LOT: Layer-wise Orthogonal Training on Improving l2 Certified Robustness »
Xiaojun Xu · Linyi Li · Bo Li -
2022 Poster: Decentralized Training of Foundation Models in Heterogeneous Environments »
Binhang Yuan · Yongjun He · Jared Davis · Tianyi Zhang · Tri Dao · Beidi Chen · Percy Liang · Christopher Ré · Ce Zhang -
2022 Poster: CoPur: Certifiably Robust Collaborative Inference via Feature Purification »
Jing Liu · Chulin Xie · Sanmi Koyejo · Bo Li -
2022 Poster: AutoML Two-Sample Test »
Jonas M. Kübler · Vincent Stimper · Simon Buchholz · Krikamol Muandet · Bernhard Schölkopf -
2022 Poster: Embrace the Gap: VAEs Perform Independent Mechanism Analysis »
Patrik Reizinger · Luigi Gresele · Jack Brady · Julius von Kügelgen · Dominik Zietlow · Bernhard Schölkopf · Georg Martius · Wieland Brendel · Michel Besserve -
2022 Poster: Active Bayesian Causal Inference »
Christian Toth · Lars Lorch · Christian Knoll · Andreas Krause · Franz Pernkopf · Robert Peharz · Julius von Kügelgen -
2022 Poster: Exploring the Limits of Domain-Adaptive Training for Detoxifying Large-Scale Language Models »
Boxin Wang · Wei Ping · Chaowei Xiao · Peng Xu · Mostofa Patwary · Mohammad Shoeybi · Bo Li · Anima Anandkumar · Bryan Catanzaro -
2022 Poster: Reduced Representation of Deformation Fields for Effective Non-rigid Shape Matching »
Ramana Subramanyam Sundararaman · Riccardo Marin · Emanuele Rodolà · Maks Ovsjanikov -
2022 Poster: Provable Benefit of Multitask Representation Learning in Reinforcement Learning »
Yuan Cheng · Songtao Feng · Jing Yang · Hong Zhang · Yingbin Liang -
2022 Poster: When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment »
Zhijing Jin · Sydney Levine · Fernando Gonzalez Adauto · Ojasv Kamal · Maarten Sap · Mrinmaya Sachan · Rada Mihalcea · Josh Tenenbaum · Bernhard Schölkopf -
2022 Poster: SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles »
Chejian Xu · Wenhao Ding · Weijie Lyu · ZUXIN LIU · Shuai Wang · Yihan He · Hanjiang Hu · DING ZHAO · Bo Li -
2022 Poster: Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees »
Jue WANG · Binhang Yuan · Luka Rimanic · Yongjun He · Tri Dao · Beidi Chen · Christopher Ré · Ce Zhang -
2022 Poster: Function Classes for Identifiable Nonlinear Independent Component Analysis »
Simon Buchholz · Michel Besserve · Bernhard Schölkopf -
2022 Poster: General Cutting Planes for Bound-Propagation-Based Neural Network Verification »
Huan Zhang · Shiqi Wang · Kaidi Xu · Linyi Li · Bo Li · Suman Jana · Cho-Jui Hsieh · J. Zico Kolter -
2022 Poster: A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits »
Ilija Bogunovic · Zihan Li · Andreas Krause · Jonathan Scarlett -
2022 Poster: Active Exploration for Inverse Reinforcement Learning »
David Lindner · Andreas Krause · Giorgia Ramponi -
2022 Poster: Will Bilevel Optimizers Benefit from Loops »
Kaiyi Ji · Mingrui Liu · Yingbin Liang · Lei Ying -
2022 Poster: pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning »
Daoyuan Chen · Dawei Gao · Weirui Kuang · Yaliang Li · Bolin Ding -
2022 Poster: Learning Long-Term Crop Management Strategies with CyclesGym »
Matteo Turchetta · Luca Corinzia · Scott Sussex · Amanda Burton · Juan Herrera · Ioannis Athanasiadis · Joachim M Buhmann · Andreas Krause -
2021 : Live Q&A Session 1 with Yoshua Bengio, Leyla Isik, Konrad Kording, Bernhard Scholkopf, Amit Sharma, Joshua Vogelstein, Weiwei Yang »
Yoshua Bengio · Leyla Isik · Konrad Kording · Bernhard Schölkopf · Joshua T Vogelstein · Weiwei Yang -
2021 : Introduction »
Weiwei Yang · Joshua T Vogelstein · Onyema Osuagwu · Soledad Villar · Johnathan Flowers · Weishung Liu · Ronan Perry · Kaleab Alemayehu Kinfu · Teresa Huang -
2021 : Dominguez Olmedo, Karimi, Schölkopf - On the Adversarial Robustness of Causal Algorithmic Recourse »
Ricardo Dominguez-Olmedo · Amir Karimi · Bernhard Schölkopf -
2021 : Panel Discussion 3 »
Taylor Webb · Hakwan Lau · Bernhard Schölkopf · Jiangying Zhou · Lior Horesh · Francesca Rossi -
2021 : Causal World Models »
Bernhard Schölkopf -
2021 : Boxhead: A Dataset for Learning Hierarchical Representations »
Yukun Chen · Andrea Dittadi · Frederik Träuble · Stefan Bauer · Bernhard Schölkopf -
2021 : Julius von Kügelgen - Independent mechanism analysis, a new concept? »
Julius von Kügelgen -
2021 Workshop: Human Centered AI »
Michael Muller · Plamen P Angelov · Shion Guha · Marina Kogan · Gina Neff · Nuria Oliver · Manuel Rodriguez · Adrian Weller -
2021 Workshop: Causal Inference & Machine Learning: Why now? »
Elias Bareinboim · Bernhard Schölkopf · Terrence Sejnowski · Yoshua Bengio · Judea Pearl -
2021 : Meta-Learning Reliable Priors in the Function Space »
Jonas Rothfuss · Dominique Heyn · jinfan Chen · Andreas Krause -
2021 : Career and Life: Panel Discussion - Bo Li, Adriana Romero-Soriano, Devi Parikh, and Emily Denton »
Remi Denton · Devi Parikh · Bo Li · Adriana Romero -
2021 : Live Q&A with Bo Li »
Bo Li -
2021 : Invited talk – Trustworthy Machine Learning via Logic Inference, Bo Li »
Bo Li -
2021 Poster: Learning Graph Models for Retrosynthesis Prediction »
Vignesh Ram Somnath · Charlotte Bunne · Connor Coley · Andreas Krause · Regina Barzilay -
2021 Poster: Risk-averse Heteroscedastic Bayesian Optimization »
Anastasia Makarova · Ilnura Usmanova · Ilija Bogunovic · Andreas Krause -
2021 Poster: Hierarchical Skills for Efficient Exploration »
Jonas Gehring · Gabriel Synnaeve · Andreas Krause · Nicolas Usunier -
2021 Poster: Federated Linear Contextual Bandits »
Ruiquan Huang · Weiqiang Wu · Jing Yang · Cong Shen -
2021 : Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models »
Boxin Wang · Chejian Xu · Shuohang Wang · Zhe Gan · Yu Cheng · Jianfeng Gao · Ahmed Awadallah · Bo Li -
2021 Poster: Dynamic Inference with Neural Interpreters »
Nasim Rahaman · Muhammad Waleed Gondal · Shruti Joshi · Peter Gehler · Yoshua Bengio · Francesco Locatello · Bernhard Schölkopf -
2021 Poster: Multi-Scale Representation Learning on Proteins »
Vignesh Ram Somnath · Charlotte Bunne · Andreas Krause -
2021 Poster: G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators »
Yunhui Long · Boxin Wang · Zhuolin Yang · Bhavya Kailkhura · Aston Zhang · Carl Gunter · Bo Li -
2021 Poster: Causal Influence Detection for Improving Efficiency in Reinforcement Learning »
Maximilian Seitzer · Bernhard Schölkopf · Georg Martius -
2021 Poster: Faster Non-asymptotic Convergence for Double Q-learning »
Lin Zhao · Huaqing Xiong · Yingbin Liang -
2021 Poster: Independent mechanism analysis, a new concept? »
Luigi Gresele · Julius von Kügelgen · Vincent Stimper · Bernhard Schölkopf · Michel Besserve -
2021 Poster: Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems »
Andreas Schlaginhaufen · Philippe Wenk · Andreas Krause · Florian Dorfler -
2021 Poster: Do Different Tracking Tasks Require Different Appearance Models? »
Zhongdao Wang · Hengshuang Zhao · Ya-Li Li · Shengjin Wang · Philip Torr · Luca Bertinetto -
2021 Poster: Information Directed Reward Learning for Reinforcement Learning »
David Lindner · Matteo Turchetta · Sebastian Tschiatschek · Kamil Ciosek · Andreas Krause -
2021 Poster: Anti-Backdoor Learning: Training Clean Models on Poisoned Data »
Yige Li · Xixiang Lyu · Nodens Koren · Lingjuan Lyu · Bo Li · Xingjun Ma -
2021 Poster: Robust Generalization despite Distribution Shift via Minimum Discriminating Information »
Tobias Sutter · Andreas Krause · Daniel Kuhn -
2021 Poster: Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning »
Scott Sussex · Caroline Uhler · Andreas Krause -
2021 Poster: Adversarial Attack Generation Empowered by Min-Max Optimization »
Jingkang Wang · Tianyun Zhang · Sijia Liu · Pin-Yu Chen · Jiacen Xu · Makan Fardad · Bo Li -
2021 Poster: Provably Faster Algorithms for Bilevel Optimization »
Junjie Yang · Kaiyi Ji · Yingbin Liang -
2021 : Real Robot Challenge II + Q&A »
Stefan Bauer · Joel Akpo · Manuel Wuethrich · Nan Rosemary Ke · Anirudh Goyal · Thomas Steinbrenner · Felix Widmaier · Annika Buchholz · Bernhard Schölkopf · Dieter Büchler · Ludovic Righetti · Franziska Meier -
2021 : Reconnaissance Blind Chess + Q&A »
Ryan Gardner · Gino Perrotta · Corey Lowman · Casey Richardson · Andrew Newman · Jared Markowitz · Nathan Drenkow · Bart Paulhamus · Ashley J Llorens · Todd Neller · Raman Arora · Bo Li · Mykel J Kochenderfer -
2021 Poster: Combating Noise: Semi-supervised Learning by Region Uncertainty Quantification »
Zhenyu Wang · Ya-Li Li · Ye Guo · Shengjin Wang -
2021 Poster: Differentiable Learning Under Triage »
Nastaran Okati · Abir De · Manuel Rodriguez -
2021 Poster: Iterative Teaching by Label Synthesis »
Weiyang Liu · Zhen Liu · Hanchen Wang · Liam Paull · Bernhard Schölkopf · Adrian Weller -
2021 Poster: Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models »
Lenart Treven · Philippe Wenk · Florian Dorfler · Andreas Krause -
2021 Poster: TRS: Transferability Reduced Ensemble via Promoting Gradient Diversity and Model Smoothness »
Zhuolin Yang · Linyi Li · Xiaojun Xu · Shiliang Zuo · Qian Chen · Pan Zhou · Benjamin Rubinstein · Ce Zhang · Bo Li -
2021 Poster: Meta-Learning Reliable Priors in the Function Space »
Jonas Rothfuss · Dominique Heyn · jinfan Chen · Andreas Krause -
2021 Poster: Counterfactual Explanations in Sequential Decision Making Under Uncertainty »
Stratis Tsirtsis · Abir De · Manuel Rodriguez -
2021 Poster: The Inductive Bias of Quantum Kernels »
Jonas Kübler · Simon Buchholz · Bernhard Schölkopf -
2021 Poster: Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization »
Chengshuai Shi · Wei Xiong · Cong Shen · Jing Yang -
2021 Poster: Backward-Compatible Prediction Updates: A Probabilistic Approach »
Frederik Träuble · Julius von Kügelgen · Matthäus Kleindessner · Francesco Locatello · Bernhard Schölkopf · Peter Gehler -
2021 Poster: Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style »
Julius von Kügelgen · Yash Sharma · Luigi Gresele · Wieland Brendel · Bernhard Schölkopf · Michel Besserve · Francesco Locatello -
2021 Poster: Misspecified Gaussian Process Bandit Optimization »
Ilija Bogunovic · Andreas Krause -
2021 Poster: DiBS: Differentiable Bayesian Structure Learning »
Lars Lorch · Jonas Rothfuss · Bernhard Schölkopf · Andreas Krause -
2021 Poster: Regret Bounds for Gaussian-Process Optimization in Large Domains »
Manuel Wuethrich · Bernhard Schölkopf · Andreas Krause -
2020 : Contributed Talk 3: Algorithmic Recourse: from Counterfactual Explanations to Interventions »
Amir-Hossein Karimi · Bernhard Schölkopf · Isabel Valera -
2020 : Invited speaker: Adaptive Sampling for Stochastic Risk-Averse Learning, Andreas Krause »
Andreas Krause -
2020 Workshop: Causal Discovery and Causality-Inspired Machine Learning »
Biwei Huang · Sara Magliacane · Kun Zhang · Danielle Belgrave · Elias Bareinboim · Daniel Malinsky · Thomas Richardson · Christopher Meek · Peter Spirtes · Bernhard Schölkopf -
2020 Workshop: Workshop on Dataset Curation and Security »
Nathalie Baracaldo · Yonatan Bisk · Avrim Blum · Michael Curry · John Dickerson · Micah Goldblum · Tom Goldstein · Bo Li · Avi Schwarzschild -
2020 Poster: Adaptive Sampling for Stochastic Risk-Averse Learning »
Sebastian Curi · Kfir Y. Levy · Stefanie Jegelka · Andreas Krause -
2020 Poster: Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters »
Kaiyi Ji · Jason Lee · Yingbin Liang · H. Vincent Poor -
2020 Poster: Contextual Games: Multi-Agent Learning with Side Information »
Pier Giuseppe Sessa · Ilija Bogunovic · Andreas Krause · Maryam Kamgarpour -
2020 Poster: Weakly Supervised Deep Functional Maps for Shape Matching »
Abhishek Sharma · Maks Ovsjanikov -
2020 Poster: Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting »
Defu Cao · Yujing Wang · Juanyong Duan · Ce Zhang · Xia Zhu · Congrui Huang · Yunhai Tong · Bixiong Xu · Jing Bai · Jie Tong · Qi Zhang -
2020 Spotlight: Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting »
Defu Cao · Yujing Wang · Juanyong Duan · Ce Zhang · Xia Zhu · Congrui Huang · Yunhai Tong · Bixiong Xu · Jing Bai · Jie Tong · Qi Zhang -
2020 Memorial: In Memory of Olivier Chapelle »
Bernhard Schölkopf · Andre Elisseeff · Olivier Bousquet · Vladimir Vapnik · Jason Weston -
2020 Poster: Learning Kernel Tests Without Data Splitting »
Jonas Kübler · Wittawat Jitkrittum · Bernhard Schölkopf · Krikamol Muandet -
2020 Poster: Coresets via Bilevel Optimization for Continual Learning and Streaming »
Zalan Borsos · Mojmir Mutny · Andreas Krause -
2020 Poster: Algorithmic recourse under imperfect causal knowledge: a probabilistic approach »
Amir-Hossein Karimi · Julius von Kügelgen · Bernhard Schölkopf · Isabel Valera -
2020 Poster: Causal analysis of Covid-19 Spread in Germany »
Atalanti Mastakouri · Bernhard Schölkopf -
2020 Poster: Model Selection for Production System via Automated Online Experiments »
Zhenwen Dai · Praveen Chandar · Ghazal Fazelnia · Benjamin Carterette · Mounia Lalmas -
2020 Poster: Gradient Estimation with Stochastic Softmax Tricks »
Max Paulus · Dami Choi · Danny Tarlow · Andreas Krause · Chris Maddison -
2020 Poster: Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations »
Huan Zhang · Hongge Chen · Chaowei Xiao · Bo Li · Mingyan Liu · Duane Boning · Cho-Jui Hsieh -
2020 Spotlight: Algorithmic recourse under imperfect causal knowledge: a probabilistic approach »
Amir-Hossein Karimi · Julius von Kügelgen · Bernhard Schölkopf · Isabel Valera -
2020 Spotlight: Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations »
Huan Zhang · Hongge Chen · Chaowei Xiao · Bo Li · Mingyan Liu · Duane Boning · Cho-Jui Hsieh -
2020 Oral: Gradient Estimation with Stochastic Softmax Tricks »
Max Paulus · Dami Choi · Danny Tarlow · Andreas Krause · Chris Maddison -
2020 Poster: Learning to Mutate with Hypergradient Guided Population »
Zhiqiang Tao · Yaliang Li · Bolin Ding · Ce Zhang · Jingren Zhou · Yun Fu -
2020 Poster: Relative gradient optimization of the Jacobian term in unsupervised deep learning »
Luigi Gresele · Giancarlo Fissore · Adrián Javaloy · Bernhard Schölkopf · Aapo Hyvarinen -
2020 Poster: Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning »
Sebastian Curi · Felix Berkenkamp · Andreas Krause -
2020 Poster: Improving Sample Complexity Bounds for (Natural) Actor-Critic Algorithms »
Tengyu Xu · Zhe Wang · Yingbin Liang -
2020 Poster: Finite-Time Analysis for Double Q-learning »
Huaqing Xiong · Lin Zhao · Yingbin Liang · Wei Zhang -
2020 Poster: Learning to Play Sequential Games versus Unknown Opponents »
Pier Giuseppe Sessa · Ilija Bogunovic · Maryam Kamgarpour · Andreas Krause -
2020 Poster: On Convergence of Nearest Neighbor Classifiers over Feature Transformations »
Luka Rimanic · Cedric Renggli · Bo Li · Ce Zhang -
2020 Poster: Correspondence learning via linearly-invariant embedding »
Riccardo Marin · Marie-Julie Rakotosaona · Simone Melzi · Maks Ovsjanikov -
2020 Spotlight: Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning »
Sebastian Curi · Felix Berkenkamp · Andreas Krause -
2020 Spotlight: Finite-Time Analysis for Double Q-learning »
Huaqing Xiong · Lin Zhao · Yingbin Liang · Wei Zhang -
2020 Poster: Safe Reinforcement Learning via Curriculum Induction »
Matteo Turchetta · Andrey Kolobov · Shital Shah · Andreas Krause · Alekh Agarwal -
2020 Spotlight: Safe Reinforcement Learning via Curriculum Induction »
Matteo Turchetta · Andrey Kolobov · Shital Shah · Andreas Krause · Alekh Agarwal -
2019 : Afternoon Coffee Break & Poster Session »
Heidi Komkov · Stanislav Fort · Zhaoyou Wang · Rose Yu · Ji Hwan Park · Samuel Schoenholz · Taoli Cheng · Ryan-Rhys Griffiths · Chase Shimmin · Surya Karthik Mukkavili · Philippe Schwaller · Christian Knoll · Yangzesheng Sun · Keiichi Kisamori · Gavin Graham · Gavin Portwood · Hsin-Yuan Huang · Paul Novello · Moritz Munchmeyer · Anna Jungbluth · Daniel Levine · Ibrahim Ayed · Steven Atkinson · Jan Hermann · Peter Grönquist · · Priyabrata Saha · Yannik Glaser · Lingge Li · Yutaro Iiyama · Rushil Anirudh · Maciej Koch-Janusz · Vikram Sundar · Francois Lanusse · Auralee Edelen · Jonas Köhler · Jacky H. T. Yip · jiadong guo · Xiangyang Ju · Adi Hanuka · Adrian Albert · Valentina Salvatelli · Mauro Verzetti · Javier Duarte · Eric Moreno · Emmanuel de Bézenac · Athanasios Vlontzos · Alok Singh · Thomas Klijnsma · Brad Neuberg · Paul Wright · Mustafa Mustafa · David Schmidt · Steven Farrell · Hao Sun -
2019 : Bernhard Schölkopf »
Bernhard Schölkopf -
2019 Workshop: Learning with Temporal Point Processes »
Manuel Rodriguez · Le Song · Isabel Valera · Yan Liu · Abir De · Hongyuan Zha -
2019 : Poster Session »
Ethan Harris · Tom White · Oh Hyeon Choung · Takashi Shinozaki · Dipan Pal · Katherine L. Hermann · Judy Borowski · Camilo Fosco · Chaz Firestone · Vijay Veerabadran · Benjamin Lahner · Chaitanya Ryali · Fenil Doshi · Pulkit Singh · Sharon Zhou · Michel Besserve · Michael Chang · Anelise Newman · Mahesan Niranjan · Jonathon Hare · Daniela Mihai · Marios Savvides · Simon Kornblith · Christina M Funke · Aude Oliva · Virginia de Sa · Dmitry Krotov · Colin Conwell · George Alvarez · Alex Kolchinski · Shengjia Zhao · Mitchell Gordon · Michael Bernstein · Stefano Ermon · Arash Mehrjou · Bernhard Schölkopf · John Co-Reyes · Michael Janner · Jiajun Wu · Josh Tenenbaum · Sergey Levine · Yalda Mohsenzadeh · Zhenglong Zhou -
2019 Workshop: Workshop on Human-Centric Machine Learning »
Plamen P Angelov · Nuria Oliver · Adrian Weller · Manuel Rodriguez · Isabel Valera · Silvia Chiappa · Hoda Heidari · Niki Kilbertus -
2019 Poster: An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors »
Janardhan Kulkarni · Olga Ohrimenko · Bolin Ding · Sergey Yekhanin · Joshua Allen · Harsha Nori -
2019 Poster: On the Fairness of Disentangled Representations »
Francesco Locatello · Gabriele Abbati · Thomas Rainforth · Stefan Bauer · Bernhard Schölkopf · Olivier Bachem -
2019 Poster: On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset »
Muhammad Waleed Gondal · Manuel Wuethrich · Djordje Miladinovic · Francesco Locatello · Martin Breidt · Valentin Volchkov · Joel Akpo · Olivier Bachem · Bernhard Schölkopf · Stefan Bauer -
2019 Poster: Efficiently Learning Fourier Sparse Set Functions »
Andisheh Amrollahi · Amir Zandieh · Michael Kapralov · Andreas Krause -
2019 Spotlight: Efficiently Learning Fourier Sparse Set Functions »
Andisheh Amrollahi · Amir Zandieh · Michael Kapralov · Andreas Krause -
2019 Poster: Stochastic Bandits with Context Distributions »
Johannes Kirschner · Andreas Krause -
2019 Poster: Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms »
Shahana Ibrahim · Xiao Fu · Nikolaos Kargas · Kejun Huang -
2019 Poster: A Domain Agnostic Measure for Monitoring and Evaluating GANs »
Paulina Grnarova · Kfir Y. Levy · Aurelien Lucchi · Nathanael Perraudin · Ian Goodfellow · Thomas Hofmann · Andreas Krause -
2019 Poster: No-Regret Learning in Unknown Games with Correlated Payoffs »
Pier Giuseppe Sessa · Ilija Bogunovic · Maryam Kamgarpour · Andreas Krause -
2019 Poster: Teaching Multiple Concepts to a Forgetful Learner »
Anette Hunziker · Yuxin Chen · Oisin Mac Aodha · Manuel Gomez Rodriguez · Andreas Krause · Pietro Perona · Yisong Yue · Adish Singla -
2019 Poster: Adaptive Sequence Submodularity »
Marko Mitrovic · Ehsan Kazemi · Moran Feldman · Andreas Krause · Amin Karbasi -
2019 Poster: Bayesian Learning of Sum-Product Networks »
Martin Trapp · Robert Peharz · Hong Ge · Franz Pernkopf · Zoubin Ghahramani -
2019 Poster: Perceiving the arrow of time in autoregressive motion »
Kristof Meding · Dominik Janzing · Bernhard Schölkopf · Felix A. Wichmann -
2019 Poster: SpiderBoost and Momentum: Faster Variance Reduction Algorithms »
Zhe Wang · Kaiyi Ji · Yi Zhou · Yingbin Liang · Vahid Tarokh -
2019 Poster: Selecting causal brain features with a single conditional independence test per feature »
Atalanti Mastakouri · Bernhard Schölkopf · Dominik Janzing -
2019 Poster: Kernel Stein Tests for Multiple Model Comparison »
Jen Ning Lim · Makoto Yamada · Bernhard Schölkopf · Wittawat Jitkrittum -
2019 Poster: Safe Exploration for Interactive Machine Learning »
Matteo Turchetta · Felix Berkenkamp · Andreas Krause -
2019 Poster: Finite-Sample Analysis for SARSA with Linear Function Approximation »
Shaofeng Zou · Tengyu Xu · Yingbin Liang -
2019 Poster: Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples »
Tengyu Xu · Shaofeng Zou · Yingbin Liang -
2019 Spotlight: Perceiving the arrow of time in autoregressive motion »
Kristof Meding · Dominik Janzing · Bernhard Schölkopf · Felix A. Wichmann -
2018 : Manuel Gomez Rodriguez - Enhancing the Accuracy and Fairness of Human Decision Making »
Manuel Rodriguez -
2018 : Datasets and Benchmarks for Causal Learning »
Csaba Szepesvari · Isabelle Guyon · Nicolai Meinshausen · David Blei · Elias Bareinboim · Bernhard Schölkopf · Pietro Perona -
2018 : Learning Independent Mechanisms »
Bernhard Schölkopf -
2018 Poster: Informative Features for Model Comparison »
Wittawat Jitkrittum · Heishiro Kanagawa · Patsorn Sangkloy · James Hays · Bernhard Schölkopf · Arthur Gretton -
2018 Poster: Convergence of Cubic Regularization for Nonconvex Optimization under KL Property »
Yi Zhou · Zhe Wang · Yingbin Liang -
2018 Spotlight: Convergence of Cubic Regularization for Nonconvex Optimization under KL Property »
Yi Zhou · Zhe Wang · Yingbin Liang -
2018 Poster: Provable Variational Inference for Constrained Log-Submodular Models »
Josip Djolonga · Stefanie Jegelka · Andreas Krause -
2018 Poster: Communication Compression for Decentralized Training »
Hanlin Tang · Shaoduo Gan · Ce Zhang · Tong Zhang · Ji Liu -
2018 Poster: Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features »
Mojmir Mutny · Andreas Krause -
2018 Poster: Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models »
Alexander Neitz · Giambattista Parascandolo · Stefan Bauer · Bernhard Schölkopf -
2018 Spotlight: Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features »
Mojmir Mutny · Andreas Krause -
2018 Poster: Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making »
Hoda Heidari · Claudio Ferrari · Krishna Gummadi · Andreas Krause -
2018 Poster: Minimax Estimation of Neural Net Distance »
Kaiyi Ji · Yingbin Liang -
2017 : Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation »
Alice Oh · Bernhard Schölkopf -
2017 : Invited talk: Towards Safe Bayesian Optimization »
Andreas Krause -
2017 Workshop: Discrete Structures in Machine Learning »
Yaron Singer · Jeff A Bilmes · Andreas Krause · Stefanie Jegelka · Amin Karbasi -
2017 Poster: Interactive Submodular Bandit »
Lin Chen · Andreas Krause · Amin Karbasi -
2017 Poster: From Parity to Preference-based Notions of Fairness in Classification »
Muhammad Bilal Zafar · Isabel Valera · Manuel Rodriguez · Krishna Gummadi · Adrian Weller -
2017 Poster: Avoiding Discrimination through Causal Reasoning »
Niki Kilbertus · Mateo Rojas Carulla · Giambattista Parascandolo · Moritz Hardt · Dominik Janzing · Bernhard Schölkopf -
2017 Poster: Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent »
Xiangru Lian · Ce Zhang · Huan Zhang · Cho-Jui Hsieh · Wei Zhang · Ji Liu -
2017 Oral: Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent »
Xiangru Lian · Ce Zhang · Huan Zhang · Cho-Jui Hsieh · Wei Zhang · Ji Liu -
2017 Poster: Safe Model-based Reinforcement Learning with Stability Guarantees »
Felix Berkenkamp · Matteo Turchetta · Angela Schoellig · Andreas Krause -
2017 Poster: Differentiable Learning of Submodular Functions »
Josip Djolonga · Andreas Krause -
2017 Spotlight: Differentiable Learning of Submodular Functions »
Josip Djolonga · Andreas Krause -
2017 Poster: Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms »
Yatao Bian · Kfir Levy · Andreas Krause · Joachim M Buhmann -
2017 Poster: Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning »
Shixiang (Shane) Gu · Timothy Lillicrap · Richard Turner · Zoubin Ghahramani · Bernhard Schölkopf · Sergey Levine -
2017 Poster: AdaGAN: Boosting Generative Models »
Ilya Tolstikhin · Sylvain Gelly · Olivier Bousquet · Carl-Johann SIMON-GABRIEL · Bernhard Schölkopf -
2017 Poster: Stochastic Submodular Maximization: The Case of Coverage Functions »
Mohammad Karimi · Mario Lucic · Hamed Hassani · Andreas Krause -
2016 Poster: Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels »
Ilya Tolstikhin · Bharath Sriperumbudur · Bernhard Schölkopf -
2016 Poster: Variational Inference in Mixed Probabilistic Submodular Models »
Josip Djolonga · Sebastian Tschiatschek · Andreas Krause -
2016 Poster: Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation »
Ilija Bogunovic · Jonathan Scarlett · Andreas Krause · Volkan Cevher -
2016 Poster: Cooperative Graphical Models »
Josip Djolonga · Stefanie Jegelka · Sebastian Tschiatschek · Andreas Krause -
2016 Poster: Fast and Provably Good Seedings for k-Means »
Olivier Bachem · Mario Lucic · Hamed Hassani · Andreas Krause -
2016 Oral: Fast and Provably Good Seedings for k-Means »
Olivier Bachem · Mario Lucic · Hamed Hassani · Andreas Krause -
2016 Poster: Safe Exploration in Finite Markov Decision Processes with Gaussian Processes »
Matteo Turchetta · Felix Berkenkamp · Andreas Krause -
2016 Poster: Consistent Kernel Mean Estimation for Functions of Random Variables »
Carl-Johann Simon-Gabriel · Adam Scibior · Ilya Tolstikhin · Bernhard Schölkopf -
2015 : Safe Exploration for Bayesian Optimization »
Andreas Krause -
2015 Poster: COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution »
Mehrdad Farajtabar · Yichen Wang · Manuel Rodriguez · Shuang Li · Hongyuan Zha · Le Song -
2015 Poster: Distributed Submodular Cover: Succinctly Summarizing Massive Data »
Baharan Mirzasoleiman · Amin Karbasi · Ashwinkumar Badanidiyuru · Andreas Krause -
2015 Poster: Sampling from Probabilistic Submodular Models »
Alkis Gotovos · Hamed Hassani · Andreas Krause -
2015 Oral: COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution »
Mehrdad Farajtabar · Yichen Wang · Manuel Rodriguez · Shuang Li · Hongyuan Zha · Le Song -
2015 Spotlight: Distributed Submodular Cover: Succinctly Summarizing Massive Data »
Baharan Mirzasoleiman · Amin Karbasi · Ashwinkumar Badanidiyuru · Andreas Krause -
2015 Oral: Sampling from Probabilistic Submodular Models »
Alkis Gotovos · Hamed Hassani · Andreas Krause -
2014 Workshop: NIPS’14 Workshop on Crowdsourcing and Machine Learning »
David Parkes · Denny Zhou · Chien-Ju Ho · Nihar Bhadresh Shah · Adish Singla · Jared Heyman · Edwin Simpson · Andreas Krause · Rafael Frongillo · Jennifer Wortman Vaughan · Panagiotis Papadimitriou · Damien Peters -
2014 Workshop: Discrete Optimization in Machine Learning »
Jeffrey A Bilmes · Andreas Krause · Stefanie Jegelka · S Thomas McCormick · Sebastian Nowozin · Yaron Singer · Dhruv Batra · Volkan Cevher -
2014 Poster: Efficient Sampling for Learning Sparse Additive Models in High Dimensions »
Hemant Tyagi · Bernd Gärtner · Andreas Krause -
2014 Poster: From MAP to Marginals: Variational Inference in Bayesian Submodular Models »
Josip Djolonga · Andreas Krause -
2014 Poster: Efficient Partial Monitoring with Prior Information »
Hastagiri P Vanchinathan · Gábor Bartók · Andreas Krause -
2014 Poster: General Stochastic Networks for Classification »
Matthias Zöhrer · Franz Pernkopf -
2014 Poster: Kernel Mean Estimation via Spectral Filtering »
Krikamol Muandet · Bharath Sriperumbudur · Bernhard Schölkopf -
2013 Workshop: Machine Learning for Sustainability »
Edwin Bonilla · Thomas Dietterich · Theodoros Damoulas · Andreas Krause · Daniel Sheldon · Iadine Chades · J. Zico Kolter · Bistra Dilkina · Carla Gomes · Hugo P Simao -
2013 Workshop: Bayesian Optimization in Theory and Practice »
Matthew Hoffman · Jasper Snoek · Nando de Freitas · Michael A Osborne · Ryan Adams · Sebastien Bubeck · Philipp Hennig · Remi Munos · Andreas Krause -
2013 Workshop: Discrete Optimization in Machine Learning: Connecting Theory and Practice »
Stefanie Jegelka · Andreas Krause · Pradeep Ravikumar · Kazuo Murota · Jeffrey A Bilmes · Yisong Yue · Michael Jordan -
2013 Workshop: Modern Nonparametric Methods in Machine Learning »
Arthur Gretton · Mladen Kolar · Samory Kpotufe · John Lafferty · Han Liu · Bernhard Schölkopf · Alexander Smola · Rob Nowak · Mikhail Belkin · Lorenzo Rosasco · peter bickel · Yue Zhao -
2013 Workshop: NIPS 2013 Workshop on Causality: Large-scale Experiment Design and Inference of Causal Mechanisms »
Isabelle Guyon · Leon Bottou · Bernhard Schölkopf · Alexander Statnikov · Evelyne Viegas · james m robins -
2013 Poster: High-Dimensional Gaussian Process Bandits »
Josip Djolonga · Andreas Krause · Volkan Cevher -
2013 Poster: The Randomized Dependence Coefficient »
David Lopez-Paz · Philipp Hennig · Bernhard Schölkopf -
2013 Poster: Statistical analysis of coupled time series with Kernel Cross-Spectral Density operators. »
Michel Besserve · Nikos K Logothetis · Bernhard Schölkopf -
2013 Poster: Causal Inference on Time Series using Restricted Structural Equation Models »
Jonas Peters · Dominik Janzing · Bernhard Schölkopf -
2013 Poster: Distributed Submodular Maximization: Identifying Representative Elements in Massive Data »
Baharan Mirzasoleiman · Amin Karbasi · Rik Sarkar · Andreas Krause -
2012 Workshop: Discrete Optimization in Machine Learning (DISCML): Structure and Scalability »
Stefanie Jegelka · Andreas Krause · Jeffrey A Bilmes · Pradeep Ravikumar -
2012 Poster: Learning from Distributions via Support Measure Machines »
Krikamol Muandet · Kenji Fukumizu · Francesco Dinuzzo · Bernhard Schölkopf -
2012 Spotlight: Learning from Distributions via Support Measure Machines »
Krikamol Muandet · Kenji Fukumizu · Francesco Dinuzzo · Bernhard Schölkopf -
2012 Poster: Semi-Supervised Domain Adaptation with Non-Parametric Copulas »
David Lopez-Paz · José Miguel Hernández-Lobato · Bernhard Schölkopf -
2012 Spotlight: Semi-Supervised Domain Adaptation with Non-Parametric Copulas »
David Lopez-Paz · José Miguel Hernández-Lobato · Bernhard Schölkopf -
2012 Poster: The representer theorem for Hilbert spaces: a necessary and sufficient condition »
Francesco Dinuzzo · Bernhard Schölkopf -
2011 Workshop: Philosophy and Machine Learning »
Marcello Pelillo · Joachim M Buhmann · Tiberio Caetano · Bernhard Schölkopf · Larry Wasserman -
2011 Workshop: Discrete Optimization in Machine Learning (DISCML): Uncertainty, Generalization and Feedback »
Andreas Krause · Pradeep Ravikumar · Stefanie S Jegelka · Jeffrey A Bilmes -
2011 Workshop: Cosmology meets Machine Learning »
Michael Hirsch · Sarah Bridle · Bernhard Schölkopf · Phil Marshall · Stefan Harmeling · Mark Girolami -
2011 Oral: Scalable Training of Mixture Models via Coresets »
Dan Feldman · Matthew Faulkner · Andreas Krause -
2011 Poster: Scalable Training of Mixture Models via Coresets »
Dan Feldman · Matthew Faulkner · Andreas Krause -
2011 Invited Talk: From kernels to causal inference »
Bernhard Schölkopf -
2011 Poster: Contextual Gaussian Process Bandit Optimization »
Andreas Krause · Cheng Soon Ong -
2011 Poster: Crowdclustering »
Ryan G Gomes · Peter Welinder · Andreas Krause · Pietro Perona -
2011 Poster: Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance »
Peter Gehler · Carsten Rother · Martin Kiefel · Lumin Zhang · Bernhard Schölkopf -
2011 Poster: Causal Discovery with Cyclic Additive Noise Models »
Joris M Mooij · Dominik Janzing · Tom Heskes · Bernhard Schölkopf -
2010 Workshop: Discrete Optimization in Machine Learning: Structures, Algorithms and Applications »
Andreas Krause · Pradeep Ravikumar · Jeffrey A Bilmes · Stefanie Jegelka -
2010 Spotlight: Switched Latent Force Models for Movement Segmentation »
Mauricio A Alvarez · Jan Peters · Bernhard Schölkopf · Neil D Lawrence -
2010 Poster: Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake »
Stefan Harmeling · Michael Hirsch · Bernhard Schölkopf -
2010 Poster: Switched Latent Force Models for Movement Segmentation »
Mauricio A Alvarez · Jan Peters · Bernhard Schölkopf · Neil D Lawrence -
2010 Poster: Probabilistic latent variable models for distinguishing between cause and effect »
Joris M Mooij · Oliver Stegle · Dominik Janzing · Kun Zhang · Bernhard Schölkopf -
2010 Spotlight: Efficient Minimization of Decomposable Submodular Functions »
Peter G Stobbe · Andreas Krause -
2010 Poster: Discriminative Clustering by Regularized Information Maximization »
Ryan G Gomes · Andreas Krause · Pietro Perona -
2010 Poster: Efficient Minimization of Decomposable Submodular Functions »
Peter G Stobbe · Andreas Krause -
2010 Poster: Near-Optimal Bayesian Active Learning with Noisy Observations »
Daniel Golovin · Andreas Krause · Debajyoti Ray -
2009 Workshop: Connectivity Inference in Neuroimaging »
Karl Friston · Moritz Grosse-Wentrup · Uta Noppeney · Bernhard Schölkopf -
2009 Workshop: Discrete Optimization in Machine Learning: Submodularity, Polyhedra and Sparsity »
Andreas Krause · Pradeep Ravikumar · Jeffrey A Bilmes -
2009 Poster: Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions »
Bharath Sriperumbudur · Kenji Fukumizu · Arthur Gretton · Gert Lanckriet · Bernhard Schölkopf -
2009 Oral: Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions »
Bharath Sriperumbudur · Kenji Fukumizu · Arthur Gretton · Gert Lanckriet · Bernhard Schölkopf -
2009 Poster: Online Learning of Assignments »
Matthew Streeter · Daniel Golovin · Andreas Krause -
2009 Spotlight: Online Learning of Assignments »
Matthew Streeter · Daniel Golovin · Andreas Krause -
2008 Workshop: Causality: objectives and assessment »
Isabelle Guyon · Dominik Janzing · Bernhard Schölkopf -
2008 Mini Symposium: Computational Photography »
Bill Freeman · Bernhard Schölkopf -
2008 Poster: Characteristic Kernels on Groups and Semigroups »
Kenji Fukumizu · Bharath Sriperumbudur · Arthur Gretton · Bernhard Schölkopf -
2008 Oral: Characteristic Kernels on Groups and Semigroups »
Kenji Fukumizu · Bharath Sriperumbudur · Arthur Gretton · Bernhard Schölkopf -
2008 Poster: Nonlinear causal discovery with additive noise models »
Patrik O Hoyer · Dominik Janzing · Joris M Mooij · Jonas Peters · Bernhard Schölkopf -
2008 Poster: Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance »
Jeremy Hill · Jason Farquhar · Suzanne Martens · Felix Bießmann · Bernhard Schölkopf -
2008 Poster: Bayesian Experimental Design of Magnetic Resonance Imaging Sequences »
Matthias Seeger · Hannes Nickisch · Rolf Pohmann · Bernhard Schölkopf -
2008 Spotlight: Nonlinear causal discovery with additive noise models »
Patrik O Hoyer · Dominik Janzing · Joris M Mooij · Jonas Peters · Bernhard Schölkopf -
2008 Spotlight: Bayesian Experimental Design of Magnetic Resonance Imaging Sequences »
Matthias Seeger · Hannes Nickisch · Rolf Pohmann · Bernhard Schölkopf -
2008 Spotlight: Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance »
Jeremy Hill · Jason Farquhar · Suzanne Martens · Felix Bießmann · Bernhard Schölkopf -
2008 Poster: An empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis »
Gabriele B Schweikert · Christian Widmer · Bernhard Schölkopf · Gunnar Rätsch -
2008 Poster: Diffeomorphic Dimensionality Reduction »
Christian Walder · Bernhard Schölkopf -
2007 Spotlight: Kernel Measures of Conditional Dependence »
Kenji Fukumizu · Arthur Gretton · Xiaohai Sun · Bernhard Schölkopf -
2007 Poster: An Analysis of Inference with the Universum »
Fabian H Sinz · Olivier Chapelle · Alekh Agarwal · Bernhard Schölkopf -
2007 Poster: Kernel Measures of Conditional Dependence »
Kenji Fukumizu · Arthur Gretton · Xiaohai Sun · Bernhard Schölkopf -
2007 Spotlight: An Analysis of Inference with the Universum »
Fabian H Sinz · Olivier Chapelle · Alekh Agarwal · Bernhard Schölkopf -
2007 Spotlight: Selecting Observations against Adversarial Objectives »
Andreas Krause · H. Brendan McMahan · Carlos Guestrin · Anupam Gupta -
2007 Spotlight: A Kernel Statistical Test of Independence »
Arthur Gretton · Kenji Fukumizu · Choon Hui Teo · Le Song · Bernhard Schölkopf · Alexander Smola -
2007 Poster: A Kernel Statistical Test of Independence »
Arthur Gretton · Kenji Fukumizu · Choon Hui Teo · Le Song · Bernhard Schölkopf · Alexander Smola -
2007 Poster: Selecting Observations against Adversarial Objectives »
Andreas Krause · H. Brendan McMahan · Carlos Guestrin · Anupam Gupta -
2006 Poster: Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions »
Christian Walder · Bernhard Schölkopf · Olivier Chapelle -
2006 Poster: Learning Dense 3D Correspondence »
Florian Steinke · Bernhard Schölkopf · Volker Blanz -
2006 Poster: A Local Learning Approach for Clustering »
Mingrui Wu · Bernhard Schölkopf -
2006 Poster: A Kernel Method for the Two-Sample-Problem »
Arthur Gretton · Karsten Borgwardt · Malte J Rasch · Bernhard Schölkopf · Alexander Smola -
2006 Poster: Correcting Sample Selection Bias by Unlabeled Data »
Jiayuan Huang · Alexander Smola · Arthur Gretton · Karsten Borgwardt · Bernhard Schölkopf -
2006 Spotlight: Correcting Sample Selection Bias by Unlabeled Data »
Jiayuan Huang · Alexander Smola · Arthur Gretton · Karsten Borgwardt · Bernhard Schölkopf -
2006 Talk: A Kernel Method for the Two-Sample-Problem »
Arthur Gretton · Karsten Borgwardt · Malte J Rasch · Bernhard Schölkopf · Alexander Smola -
2006 Poster: A Nonparametric Approach to Bottom-Up Visual Saliency »
Wolf Kienzle · Felix A Wichmann · Bernhard Schölkopf · Matthias Franz -
2006 Poster: Learning with Hypergraphs: Clustering, Classification, and Embedding »
Denny Zhou · Jiayuan Huang · Bernhard Schölkopf