ICML event header - abstract blue circles

2022年7月17日 – 2022年7月23日

Microsoft at ICML 2022

Eastern Daylight Time (UTC – 4)

地点： Baltimore, MD

08:00 – 19:00 Workshop

LatinX in AI (LXAI) LXAI Research Workshop Proposal

Maria Luisa Santiago, Juan Miguel Gutierrez Vidal, Fanny Nina Paravecino, CJ Barbearn, Julio Hurtado, Andres Marquez, Jose M. Saavedra, Javier A Orduz, Wayner Barrios

Sponsored by Microsoft
08:30 – 18:40 Workshop

Women in Machine Learning (WiML)

Vinitra Swamy, Paula Gradu, Mojgan Saeidi, Noor Sajid, Shweta Khushu, Giulia Clerici, Tatjana Chavdarova

Sponsored by Microsoft
09:00 – 16:35 Workshop

New In Machine Learning (NewInML)

Alice Lacan, Mélina Verger
13:00 – 15:00 Tutorial

Bridging Learning and Decision Making

Dylan Foster, Alexander Rakhlin

10:30 – 12:00 Talk session

Spotlight: Reinforcement Learning
相关论文与出版物
- Provable Reinforcement Learning with a Short-Term Memory
  
  Yonathan Efroni, Chi Jin, Akshay Krishnamurthy, Sobhan Miryoosefi
10:30 – 12:00 Talk session

Spotlight: Theory: Online Learning/Bandits
相关论文与出版物
- Simultaneously Learning Stochastic and Adversarial Bandits with General Graph Feedback
  
  Fang Kong, Yichi Zhou, Shuai Li
- Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models
  
  Viktor Bengs, Aadirupa Saha, Eyke Hüllermeier
- Optimal and Efficient Dynamic Regret Algorithms for Non-Stationary Dueling Bandits
  
  Aadirupa Saha, Shubham Gupta
- Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback
  
  Darren Lin, Aldo Pacchiano, Yaodong Yu, Michael Jordan
10:30 – 12:00 Talk session

Spotlight: Deep Learning
相关论文与出版物
- Analyzing and Mitigating Interference in Neural Architecture Search
  
  Jin Xu, Xu Tan, Kaitao Song, Renqian Luo, Yichong Leng, Tao Qin, Tie-Yan Liu, Sujian Li
10:30 – 12:00 Talk session

Spotlight: Deep Learning: Generative Models/Autoencoders
相关论文与出版物
- DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale
  
  Samyam Rajbhandari, Conglong Li, Zhewei Yao, Minjia Zhang, Reza Yazdani Aminabadi, Ammar Ahmad Awan, Jeff Rasley, Yuxiong He
10:30 – 12:00 Talk session

Oral: Deep Learning: Generative Models/Autoencoders
相关论文与出版物
- Equivariant Diffusion for Molecule Generation in 3D
  
  Emiel Hoogeboom, Victor Garcia Satorras, Clément Vignac, Max Welling
13:30 – 15:00 Talk session

Spotlight: SA: Accountability, Transparency and Interpretability
相关论文与出版物
- Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments
  
  Anqi Zhang, Jinkun Lin, Aurojit Panda, Jinyang Li, Mathias Lécuyer, Siddhartha Sen
13:30 – 15:00 Talk session

Oral: Reinforcement Learning: Deep/Batch/Offline
相关论文与出版物
- Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution
  
  Vihang Patil, Markus Hofmarcher, Marius-Constantin Dinu, Matthias Dorfer, Patrick Blies, Johannes Brandstetter, Jose A. Arjona-Medina, Sepp Hochreiter
13:30 – 15:00 Talk session

Spotlight: Reinforcement Learning: Deep/Batch/Offline
相关论文与出版物
- Supervised Off-Policy Ranking
  
  Yue Jin, Yue Zhang, Tao Qin, Xudong Zhang, Jian Yuan, Houqiang Li, Tie-Yan Liu
13:30 – 15:00 Talk session

Spotlight: DL: Graph Neural Networks
相关论文与出版物
- HousE: Knowledge Graph Embedding with Householder Parameterization
  
  Rui Li, Chaozhuo Li, Jianan Zhao, Di He, Yiqi Wang, Yuming Liu, Hao Sun, Senzhang Wang, Weiwei Deng, Yanming Shen, Xing Xie, Qi Zhang
13:30 – 15:00 Talk session

Spotlight: Theory: Bandits/RL/Everything Else
相关论文与出版物
- Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms
  
  Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
16:15 – 17:45 Talk session

Spotlight: Deep Learning
相关论文与出版物
- Going Deeper into Permutation-Sensitive Graph Neural Networks
  
  Zhongyu Huang, Yingheng Wang, Chaozhuo Li, Huiguang He
16:15 – 17:45 Talk session

Spotlight: MISC: Causality
相关论文与出版物
- Matching Learned Causal Effects of Neural Networks with Domain Priors
  
  Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N Balasubramainan, Amit Sharma
16:15 – 17:45 Talk session

Spotlight: T: Learning/Deep Learning Theory
相关论文与出版物
- Inductive Biases and Variable Creation in Self-Attention Mechanisms
  
  Benjamin Edelman, Surbhi Goel, Sham Kakade, Cyril Zhang
16:15 – 17:45 Talk session

Spotlight: APP: Neuroscience, Cognitive Science
相关论文与出版物
- Bayesian Nonparametric Learning for Point Processes with Spatial Homogeneity: A Spatial Analysis of NBA Shot Locations
  
  Fan Yin, Jieying Jiao, Guanyu Hu, Jun Yan
16:15 – 17:45 Talk session

Oral: APP: Neuroscience, Cognitive Science
相关论文与出版物
- Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness
  
  Adam Foster, Arpi Vezer, Craig Glastonbury, Páidí Creed, Sam Abujudeh, Aaron Sim
16:15 – 17:45 Talk session

Spotlight: PM: Monte Carlo and Sampling Methods
相关论文与出版物
- Scalable Spike-and-Slab
  
  Niloy Biswas, Lester Mackey, Xiao-Li Meng
16:15 – 17:45 Talk session

Oral: Theory
18:30 – 20:30 Poster session

Poster Session 1
相关论文与出版物
- Bayesian Nonparametric Learning for Point Processes with Spatial Homogeneity: A Spatial Analysis of NBA Shot Locations
  
  Fan Yin, Jieying Jiao, Guanyu Hu, Jun Yan
- Analyzing and Mitigating Interference in Neural Architecture Search
  
  Jin Xu, Xu Tan, Kaitao Song, Renqian Luo, Yichong Leng, Tao Qin, Tie-Yan Liu, Sujian Li
- DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale
  
  Samyam Rajbhandari, Conglong Li, Zhewei Yao, Minjia Zhang, Reza Yazdani Aminabadi, Ammar Ahmad Awan, Jeff Rasley, Yuxiong He
- Equivariant Diffusion for Molecule Generation in 3D
  
  Emiel Hoogeboom, Victor Garcia Satorras, Clément Vignac, Max Welling
- HousE: Knowledge Graph Embedding with Householder Parameterization
  
  Rui Li, Chaozhuo Li, Jianan Zhao, Di He, Yiqi Wang, Yuming Liu, Hao Sun, Senzhang Wang, Weiwei Deng, Yanming Shen, Xing Xie, Qi Zhang
- Going Deeper into Permutation-Sensitive Graph Neural Networks
  
  Zhongyu Huang, Yingheng Wang, Chaozhuo Li, Huiguang He
- Matching Learned Causal Effects of Neural Networks with Domain Priors
  
  Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N Balasubramainan, Amit Sharma
- Scalable Spike-and-Slab
  
  Niloy Biswas, Lester Mackey, Xiao-Li Meng
- Provable Reinforcement Learning with a Short-Term Memory
  
  Yonathan Efroni, Chi Jin, Akshay Krishnamurthy, Sobhan Miryoosefi
- Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution
  
  Vihang Patil, Markus Hofmarcher, Marius-Constantin Dinu, Matthias Dorfer, Patrick Blies, Johannes Brandstetter, Jose A. Arjona-Medina, Sepp Hochreiter
- Supervised Off-Policy Ranking
  
  Yue Jin, Yue Zhang, Tao Qin, Xudong Zhang, Jian Yuan, Houqiang Li, Tie-Yan Liu
- Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments
  
  Anqi Zhang, Jinkun Lin, Aurojit Panda, Jinyang Li, Mathias Lécuyer, Siddhartha Sen
- Simultaneously Learning Stochastic and Adversarial Bandits with General Graph Feedback
  
  Fang Kong, Yichi Zhou, Shuai Li
- Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms
  
  Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
- Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness
  
  Adam Foster, Arpi Vezer, Craig Glastonbury, Páidí Creed, Sam Abujudeh, Aaron Sim
- Inductive Biases and Variable Creation in Self-Attention Mechanisms
  
  Benjamin Edelman, Surbhi Goel, Sham Kakade, Cyril Zhang
- Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models
  
  Viktor Bengs, Aadirupa Saha, Eyke Hüllermeier
- Optimal and Efficient Dynamic Regret Algorithms for Non-Stationary Dueling Bandits
  
  Aadirupa Saha, Shubham Gupta
- Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback
  
  Darren Lin, Aldo Pacchiano, Yaodong Yu, Michael Jordan

10:30 – 12:00 Talk session

Oral: Deep Learning
相关论文与出版物
- Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum
  
  Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, Masashi Sugiyama
10:30 – 12:00 Talk session

Spotlight: Deep Learning
相关论文与出版物
- On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features
  
  Jinxin Zhou, Xiao Li, Tianyu Ding, Chong You, Qing Qu, Zhihui Zhu
10:30 – 12:00 Talk session

Spotlight: T: Learning Theory/Domain Adaptation
相关论文与出版物
- Contextual Bandits with Large Action Spaces: Made Practical
  
  Yinglun Zhu, Dylan Foster, John Langford, Paul Mineiro
10:30 – 12:00 Talk session

Spotlight: DL: Theory
相关论文与出版物
- Data Augmentation as Feature Manipulation
  
  Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar
- Understanding Contrastive Learning Requires Incorporating Inductive Biases
  
  Nikunj Umesh Saunshi, Jordan Ash, Surbhi Goel, Dipendra Kumar Misra, Cyril Zhang, Sanjeev Arora, Sham Kakade, Akshay Krishnamurthy
- SE(3) Equivariant Graph Neural Networks with Complete Local Frames
  
  weitao du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Tie-Yan Liu, Nanning Zheng, Bin Shao
10:30 – 12:00 Talk session

Spotlight: OPT: First Order
相关论文与出版物
- Personalization Improves Privacy-Accuracy Tradeoffs in Federated Optimization
  
  Alberto Bietti, Chen-Yu Wei, Miro Dudík, John Langford, Steven Wu
13:15 – 14:45 Talk session

Spotlight: Theory
相关论文与出版物
- Interactively Learning Preference Constraints in Linear Bandits
  
  David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
13:15 – 14:45 Talk session

Oral: MISC: Representation Learning/Causality
相关论文与出版物
- RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests
  
  Victor Chernozhukov, Whitney K. Newey, Victor Quintas-Martinez, Vasilis Syrgkanis
13:15 – 14:45 Talk session

Spotlight: DL: Robustness
相关论文与出版物
- Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  
  Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo, Dongsheng Li, Weining Qian
14:30 – 16:00 Talk session

Spotlight: Applications
相关论文与出版物
- PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance
  
  Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao
14:30 – 16:00 Talk session

Spotlight: Reinforcement Learning
相关论文与出版物
- Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods
  
  Yi Wan, Harm van Seijen, Ida Momennejad, Sarath Chandar, Janarthanan Rajendran, Ali Rahimi-Kalahroudi
14:30 – 16:00 Talk session

Spotlight: Miscellaneous Aspects of Machine Learning/Reinforcement Learning
相关论文与出版物
- Sparsity in Partially Controllable Linear Systems
  
  Yonathan Efroni, Sham Kakade, Akshay Krishnamurthy, Cyril Zhang
14:30 – 16:00 Talk session

Spotlight: Deep Learning/Optimization
相关论文与出版物
- Gating Dropout: Communication-efficient Regularization for Sparsely Activated Transformers
  
  Rui Liu, Young Jin Kim, Alexandre Muzio, Hany Hassan Awadalla
18:30 – 20:30 Poster session

Poster Session 2
相关论文与出版物
- PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance
  
  Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao
- Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum
  
  Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, Masashi Sugiyama
- On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features
  
  Jinxin Zhou, Xiao Li, Tianyu Ding, Chong You, Qing Qu, Zhihui Zhu
- Data Augmentation as Feature Manipulation
  
  Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar
- Understanding Contrastive Learning Requires Incorporating Inductive Biases
  
  Nikunj Umesh Saunshi, Jordan Ash, Surbhi Goel, Dipendra Kumar Misra, Cyril Zhang, Sanjeev Arora, Sham Kakade, Akshay Krishnamurthy
- SE(3) Equivariant Graph Neural Networks with Complete Local Frames
  
  weitao du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Tie-Yan Liu, Nanning Zheng, Bin Shao
- Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  
  Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo, Dongsheng Li, Weining Qian
- Gating Dropout: Communication-efficient Regularization for Sparsely Activated Transformers
  
  Rui Liu, Young Jin Kim, Alexandre Muzio, Hany Hassan Awadalla
- Personalization Improves Privacy-Accuracy Tradeoffs in Federated Optimization
  
  Alberto Bietti, Chen-Yu Wei, Miro Dudík, John Langford, Steven Wu
- Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods
  
  Yi Wan, Harm van Seijen, Ida Momennejad, Sarath Chandar, Janarthanan Rajendran, Ali Rahimi-Kalahroudi
- Sparsity in Partially Controllable Linear Systems
  
  Yonathan Efroni, Sham Kakade, Akshay Krishnamurthy, Cyril Zhang
- Contextual Bandits with Large Action Spaces: Made Practical
  
  Yinglun Zhu, Dylan Foster, John Langford, Paul Mineiro
- Interactively Learning Preference Constraints in Linear Bandits
  
  David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
- RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests
  
  Victor Chernozhukov, Whitney K. Newey, Victor Quintas-Martinez, Vasilis Syrgkanis

10:30 – 12:00 Talk session

Spotlight: T: Bandits/Online Learning/Reinforcement Learning
相关论文与出版物
- Branching Reinforcement Learning
  
  Yihan Du, Wei Chen
10:30 – 12:00 Talk session

Spotlight: APP: Physics/Computer Vision
相关论文与出版物
- An Intriguing Property of Geophysics Inversion
  
  Yinan Feng, Yinpeng Chen, Shihang Feng, Peng Jin, Zicheng Liu, Youzuo Lin
10:30 – 12:00 Talk session

Spotlight: Optimization/Reinforcement Learning
相关论文与出版物
- A Framework for Learning to Request Rich and Contextually Useful Information from Humans
  
  Khanh Nguyen, Yonatan Bisk, Hal Daumé III
13:30 – 15:00 Talk session

Spotlight: Deep Learning: Attention Mechanisms
相关论文与出版物
- NeuralEF: Deconstructing Kernels by Deep Neural Networks
  
  Zhijie Deng, Jiaxin Shi, Jun Zhu
- Visual Attention Emerges from Recurrent Sparse Reconstruction
  
  Baifeng Shi, Yale Song, Neel Joshi, Xin Wang, Trevor Darrell
13:30 – 15:00 Talk session

Oral: Reinforcement Learning
相关论文与出版物
- Adversarially Trained Actor Critic for Offline Reinforcement Learning
  
  Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal
13:30 – 15:00 Talk session

Spotlight: Deep Learning/MISC
相关论文与出版物
- Lie Point Symmetry Data Augmentation for Neural PDE Solvers
  
  Johannes Brandstetter, Max Welling, Daniel E. Worrall
13:30 – 15:00 Talk session

Spotlight: Reinforcement Learning
相关论文与出版物
- Transformers are Meta-Reinforcement Learners
  
  Luckeciano Carvalho Melo
15:30 – 17:00 Talk session

Spotlight: T: Online Learning and Bandits
相关论文与出版物
- Universal and data-adaptive algorithms for model selection in linear contextual bandits
  
  Vidya Muthukumar, Akshay Krishnamurthy
- Versatile Dueling Bandits: Best-of-both World Analyses for Learning from Relative Preferences
  
  Aadirupa Saha, Pierre Gaillard
15:30 – 17:00 Talk session

Spotlight: Applications/Optimization
相关论文与出版物
- NP-Match: When Neural Processes meet Semi-Supervised Learning
  
  Jianfeng Wang, Thomas Lukasiewicz, Xiaolin Hu, Daniela Massiceti, Vladimir Pavlovic, Alexandros Neophytou
15:30 – 17:00 Talk session

Spotlight: Optimization/Reinforcement Learning
相关论文与出版物
- On the Hidden Biases of Policy Mirror Ascent in Continuous Action Spaces
  
  Amrit Singh Bedi, Souradip Chakraborty, Anjaly Parayil, Brian Sadler, Pratap Tokekar, Alec Koppel
- Asking for Knowledge (AFK): Training RL Agents to Query External Knowledge Using Language
  
  Iou-Jen Liu, Xingdi Yuan, Marc-Alexandre Côté, Pierre-Yves Oudeyer, Alex Schwing
15:30 – 17:00 Talk session

Spotlight: Social Aspects/Optimization
相关论文与出版物
- A Convergence Theory for SVGD in the Population Limit under Talagrand's Inequality T1
  
  Adil Salim, Lukang Su, Peter Richtarik
18:00 – 20:00 Talk session

Poster Session 3
相关论文与出版物
- An Intriguing Property of Geophysics Inversion
  
  Yinan Feng, Yinpeng Chen, Shihang Feng, Peng Jin, Zicheng Liu, Youzuo Lin
- NP-Match: When Neural Processes meet Semi-Supervised Learning
  
  Jianfeng Wang, Thomas Lukasiewicz, Xiaolin Hu, Daniela Massiceti, Vladimir Pavlovic, Alexandros Neophytou
- NeuralEF: Deconstructing Kernels by Deep Neural Networks
  
  Zhijie Deng, Jiaxin Shi, Jun Zhu
- Visual Attention Emerges from Recurrent Sparse Reconstruction
  
  Baifeng Shi, Yale Song, Neel Joshi, Xin Wang, Trevor Darrell
- Lie Point Symmetry Data Augmentation for Neural PDE Solvers
  
  Johannes Brandstetter, Max Welling, Daniel E. Worrall
- A Convergence Theory for SVGD in the Population Limit under Talagrand's Inequality T1
  
  Adil Salim, Lukang Su, Peter Richtarik
- A Framework for Learning to Request Rich and Contextually Useful Information from Humans
  
  Khanh Nguyen, Yonatan Bisk, Hal Daumé III
- Adversarially Trained Actor Critic for Offline Reinforcement Learning
  
  Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal
- Transformers are Meta-Reinforcement Learners
  
  Luckeciano Carvalho Melo
- On the Hidden Biases of Policy Mirror Ascent in Continuous Action Spaces
  
  Amrit Singh Bedi, Souradip Chakraborty, Anjaly Parayil, Brian Sadler, Pratap Tokekar, Alec Koppel
- Asking for Knowledge (AFK): Training RL Agents to Query External Knowledge Using Language
  
  Iou-Jen Liu, Xingdi Yuan, Marc-Alexandre Côté, Pierre-Yves Oudeyer, Alex Schwing
- Branching Reinforcement Learning
  
  Yihan Du, Wei Chen
- Universal and data-adaptive algorithms for model selection in linear contextual bandits
  
  Vidya Muthukumar, Akshay Krishnamurthy
- Versatile Dueling Bandits: Best-of-both World Analyses for Learning from Relative Preferences
  
  Aadirupa Saha, Pierre Gaillard

08:45 – 18:00 Workshop

Beyond Bayes: Paths Towards Universal Reasoning Systems

Zenna Tavares, Emily Mackevicius, Elias Bingham, Nan Rosemary Ke, Talia Ringer, Armando Solar-Lezama, Nada Amin, John Krakauer, Robert Osazuwa Ness
08:45 – 18:00 Workshop

DataPerf: Benchmarking Data for Data-Centric AI

Lora Aroyo, Newsha Ardalani, Colby Banbury, Gregory Diamos, William Gaviria Rojas, Tzu-Sheng Kuo, Mark Mazumder, Peter Mattson, Praveen Paritosh

Invited Speaker: Beshmira Nushi
08:45 – 18:30 Workshop

ICML workshop on Machine Learning for Cybersecurity

John Emanuello, Andy Applebaum, William Arbaugh, Jack Davidson, Joseph Edappully, H. Howie Huang, Andrew Golczynski, Nicole Nichols, Tejas Patel, Ahmad Ridley, Vance Wong

Program Committee: Hyrum Anderson
08:45 – 19:30 Workshop

Spurious correlations, Invariance, and Stability (SCIS)

Aahlad Puli, Maggie Makar, Victor Veitch, Yoav Wald, Mark Goldstein, Limor Gultchin, Angela Zhou, Uri Shalit, Suchi Saria
相关论文与出版物
- Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization
  
  Jivat Neet Kaur, Emre Kiciman, Amit Sharma
09:00 – 18:00 Workshop

Theory and Practice of Differential Privacy

Gautam Kamath, Audra McMillan

Organizing and Program Committee: Huishuai Zhang

08:45 – 18:10 Workshop

Complex feedback in online learning

Rémy Degenne, Pierre Gaillard, Wouter Koolen, Aadirupa Saha
08:55 – 17:30 Workshop

Updatable Machine Learning

Ayush Sekhari, Gautam Kamath, Jayadev Acharya

Program Committee: Da Yu
09:00 – 17:30 Workshop

Responsible Decision Making in Dynamic Environments

Virginie Do, Thorsten Joachims, Alessandro Lazaric, Joelle Pineau, Matteo Pirotta, Harsh Satija, Nicolas Usunier

Invited Speaker: Solon Barocas
09:00 – 18:00 Workshop

Continuous Time Perspectives in Machine Learning

Mihaela Rosca, Chongli Qin, Julien Mairal, Marc Deisenroth

Panelist: Adil Salim
09:15 – 17:30 Workshop

2nd Workshop on Interpretable Machine Learning in Healthcare (IMLH)

Ramin Zabih, S. Kevin Zhou, Weina Jin, Yuyin Zhou, Ipek Oguz, Xiaoxiao Li, Yifan Peng, Zongwei Zhou, Yucheng Tang

Speaker: Rich Caruana
09:15 – 15:00 Workshop

Queer in AI @ ICML 2022 Affinity Workshop

Huan Zhang, Arjun Subramonian, Sharvani Jha, William Agnew, Kruno Lehman

Sponsored by Microsoft

Microsoft at ICML 2022

Monday, July 18, 2022

Bridging Learning and Decision Making

Tuesday, July 19, 2022

Spotlight: Reinforcement Learning

Spotlight: Theory: Online Learning/Bandits

Spotlight: Deep Learning

Spotlight: Deep Learning: Generative Models/Autoencoders

Oral: Deep Learning: Generative Models/Autoencoders

Spotlight: SA: Accountability, Transparency and Interpretability

Oral: Reinforcement Learning: Deep/Batch/Offline

Spotlight: Reinforcement Learning: Deep/Batch/Offline

Spotlight: DL: Graph Neural Networks

Spotlight: Theory: Bandits/RL/Everything Else

Spotlight: Deep Learning

Spotlight: MISC: Causality

Spotlight: T: Learning/Deep Learning Theory

Spotlight: APP: Neuroscience, Cognitive Science

Oral: APP: Neuroscience, Cognitive Science

Spotlight: PM: Monte Carlo and Sampling Methods

Oral: Theory

Poster Session 1

Wednesday, July 20, 2022

Oral: Deep Learning

Spotlight: Deep Learning

Spotlight: T: Learning Theory/Domain Adaptation

Spotlight: DL: Theory

Spotlight: OPT: First Order

Spotlight: Theory

Oral: MISC: Representation Learning/Causality

Spotlight: DL: Robustness

Spotlight: Applications

Spotlight: Reinforcement Learning

Spotlight: Miscellaneous Aspects of Machine Learning/Reinforcement Learning

Spotlight: Deep Learning/Optimization

Poster Session 2

Thursday, July 21, 2022

Spotlight: T: Bandits/Online Learning/Reinforcement Learning

Spotlight: APP: Physics/Computer Vision

Spotlight: Optimization/Reinforcement Learning

Spotlight: Deep Learning: Attention Mechanisms

Oral: Reinforcement Learning

Spotlight: Deep Learning/MISC

Spotlight: Reinforcement Learning

Spotlight: T: Online Learning and Bandits

Spotlight: Applications/Optimization

Spotlight: Optimization/Reinforcement Learning

Spotlight: Social Aspects/Optimization

Poster Session 3

Friday, July 22, 2022

Saturday, July 23, 2022