A Convergence Theory for SVGD in the Population Limit under Talagrand’s Inequality T1
Adil Salim, Lukang Su, Peter Richtarik
ICML 2022 | July 2022
July 17, 2022 –
July 23, 2022
Microsoft at ICML 2022
Eastern Daylight Time (UTC – 4)
Location: Baltimore, MD
Publications
Publications by Year
-
A Framework for Learning to Request Rich and Contextually Useful Information from Humans
Khanh Nguyen, Yonatan Bisk, Hal Daumé III
ICML 2022 | July 2022
Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum
Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, Masashi Sugiyama
ICML 2022 | July 2022
Adversarially Trained Actor Critic for Offline Reinforcement Learning
Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal
ICML 2022 | July 2022
Outstanding Paper Runner Up Award
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
ICML 2022 | July 2022
An Intriguing Property of Geophysics Inversion
Yinan Feng, Yinpeng Chen, Shihang Feng, Peng Jin, Zicheng Liu, Youzuo Lin
ICML 2022 | July 2022
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
ICML 2022 | July 2022
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
ICML 2022 | July 2022
Bayesian Nonparametric Learning for Point Processes with Spatial Homogeneity: A Spatial Analysis of NBA Shot Locations
Fan Yin, Jieying Jiao, Guanyu Hu, Jun Yan
ICML 2022 | July 2022
Branching Reinforcement Learning
Yihan Du, Wei Chen
Proceedings of the 39th International Conference on Machine Learning (ICML) | July 2022
Contextual Bandits with Large Action Spaces: Made Practical
Yinglun Zhu, Dylan Foster, John Langford, Paul Mineiro
2022 International Conference on Machine Learning | July 2022
Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness
Adam Foster, Arpi Vezer, Craig Glastonbury, Páidí Creed, Sam Abujudeh, Aaron Sim
ICML 2022 | July 2022
Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
ICML 2022 | July 2022
Data Augmentation as Feature Manipulation
Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar
ICML 2022 | July 2022
Equivariant Diffusion for Molecule Generation in 3D
Emiel Hoogeboom, Victor Garcia Satorras, Clément Vignac, Max Welling
ICML 2022 | July 2022
Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo, Dongsheng Li, Weining Qian
ICML 2022 | July 2022
Gating Dropout: Communication-efficient Regularization for Sparsely Activated Transformers
Rui Liu, Young Jin Kim, Alexandre Muzio, Hany Hassan Awadalla
ICML 2022 | July 2022
Matching Learned Causal Effects of Neural Networks with Domain Priors
Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N Balasubramainan, Amit Sharma
ICML 2022 | July 2022
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
ICML 2022 | July 2022
NeuralEF: Deconstructing Kernels by Deep Neural Networks
Zhijie Deng, Jiaxin Shi, Jun Zhu
ICML 2022 | July 2022
Non-Stationary Dueling Bandits
Aadirupa Saha, Shubham Gupta
ICML 2022 | July 2022
NP-Match: When Neural Processes meet Semi-Supervised Learning
Jianfeng Wang, Thomas Lukasiewicz, Xiaolin Hu, Daniela Massiceti, Vladimir Pavlovic, Alexandros Neophytou
ICML 2022 | July 2022
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
ICML 2022 | July 2022
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
ICML 2022 | July 2022
Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback
Darren Lin, Aldo Pacchiano, Yaodong Yu, Michael Jordan
ICML 2022 | July 2022
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Optimization
Alberto Bietti, Chen-Yu Wei, Miro Dudík, John Langford, Steven Wu
ICML 2022 | July 2022
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
ICML 2022 | July 2022
Provable Reinforcement Learning with a Short-Term Memory
Yonathan Efroni, Chi Jin, Akshay Krishnamurthy, Sobhan Miryoosefi
ICML 2022 | July 2022
RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests
Victor Chernozhukov, Whitney K. Newey, Victor Quintas-Martinez, Vasilis Syrgkanis
ICML 2022 | July 2022
Scalable Spike-and-Slab
Niloy Biswas, Lester Mackey, Xiao-Li Meng
ICML 2022 | July 2022
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
ICML 2022 | July 2022
Simultaneously Learning Stochastic and Adversarial Bandits with General Graph Feedback
Fang Kong, Yichi Zhou, Shuai Li
ICML 2022 | July 2022
Sparsity in Partially Controllable Linear Systems
Yonathan Efroni, Sham Kakade, Akshay Krishnamurthy, Cyril Zhang
ICML 2022 | July 2022
Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models
Viktor Bengs, Aadirupa Saha, Eyke Hüllermeier
ICML 2022 | July 2022
Supervised Off-Policy Ranking
Yue Jin, Yue Zhang, Tao Qin, Xudong Zhang, Jian Yuan, Houqiang Li, Tie-Yan Liu
ICML 2022 | July 2022
Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods
Yi Wan, Harm van Seijen, Ida Momennejad, Sarath Chandar, Janarthanan Rajendran, Ali Rahimi-Kalahroudi
ICML 2022 | July 2022
Transformers are Meta-Reinforcement Learners
Luckeciano Carvalho Melo
ICML 2022 | July 2022
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
ICML 2022 | July 2022
Universal and data-adaptive algorithms for model selection in linear contextual bandits
Vidya Muthukumar, Akshay Krishnamurthy
ICML 2022 | July 2022
Versatile Dueling Bandits: Best-of-both World Analyses for Learning from Relative Preferences
Aadirupa Saha, Pierre Gaillard
ICML 2022 | July 2022
Visual Attention Emerges from Recurrent Sparse Reconstruction
Baifeng Shi, Yale Song, Neel Joshi, Xin Wang, Trevor Darrell
ICML 2022 | July 2022
Going Deeper into Permutation-Sensitive Graph Neural Networks
Zhongyu Huang, Yingheng Wang, Chaozhuo Li, Huiguang He
ICML 2022 | June 2022
Inductive Biases and Variable Creation in Self-Attention Mechanisms
Benjamin Edelman, Surbhi Goel, Sham Kakade, Cyril Zhang
ICML 2022 | June 2022
Interactively Learning Preference Constraints in Linear Bandits
David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
ICML 2022 | June 2022
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
ICML 2022 | May 2022
Lie Point Symmetry Data Augmentation for Neural PDE Solvers
Johannes Brandstetter, Max Welling, Daniel E. Worrall
ICML 2022 | February 2022
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
ICML 2022 | January 2022
Publications by Research Area
-
Contextual Bandits with Large Action Spaces: Made Practical
Yinglun Zhu, Dylan Foster, John Langford, Paul Mineiro
2022 International Conference on Machine Learning | July 2022
A Convergence Theory for SVGD in the Population Limit under Talagrand’s Inequality T1
Adil Salim, Lukang Su, Peter Richtarik
ICML 2022 | July 2022
NP-Match: When Neural Processes meet Semi-Supervised Learning
Jianfeng Wang, Thomas Lukasiewicz, Xiaolin Hu, Daniela Massiceti, Vladimir Pavlovic, Alexandros Neophytou
ICML 2022 | July 2022
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
ICML 2022 | July 2022
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
ICML 2022 | July 2022
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
ICML 2022 | July 2022
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
ICML 2022 | July 2022
Visual Attention Emerges from Recurrent Sparse Reconstruction
Baifeng Shi, Yale Song, Neel Joshi, Xin Wang, Trevor Darrell
ICML 2022 | July 2022
Versatile Dueling Bandits: Best-of-both World Analyses for Learning from Relative Preferences
Aadirupa Saha, Pierre Gaillard
ICML 2022 | July 2022
Universal and data-adaptive algorithms for model selection in linear contextual bandits
Vidya Muthukumar, Akshay Krishnamurthy
ICML 2022 | July 2022
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
ICML 2022 | July 2022
Transformers are Meta-Reinforcement Learners
Luckeciano Carvalho Melo
ICML 2022 | July 2022
Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods
Yi Wan, Harm van Seijen, Ida Momennejad, Sarath Chandar, Janarthanan Rajendran, Ali Rahimi-Kalahroudi
ICML 2022 | July 2022
Supervised Off-Policy Ranking
Yue Jin, Yue Zhang, Tao Qin, Xudong Zhang, Jian Yuan, Houqiang Li, Tie-Yan Liu
ICML 2022 | July 2022
Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models
Viktor Bengs, Aadirupa Saha, Eyke Hüllermeier
ICML 2022 | July 2022
Sparsity in Partially Controllable Linear Systems
Yonathan Efroni, Sham Kakade, Akshay Krishnamurthy, Cyril Zhang
ICML 2022 | July 2022
Simultaneously Learning Stochastic and Adversarial Bandits with General Graph Feedback
Fang Kong, Yichi Zhou, Shuai Li
ICML 2022 | July 2022
Scalable Spike-and-Slab
Niloy Biswas, Lester Mackey, Xiao-Li Meng
ICML 2022 | July 2022
Provable Reinforcement Learning with a Short-Term Memory
Yonathan Efroni, Chi Jin, Akshay Krishnamurthy, Sobhan Miryoosefi
ICML 2022 | July 2022
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Optimization
Alberto Bietti, Chen-Yu Wei, Miro Dudík, John Langford, Steven Wu
ICML 2022 | July 2022
Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback
Darren Lin, Aldo Pacchiano, Yaodong Yu, Michael Jordan
ICML 2022 | July 2022
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
ICML 2022 | July 2022
Non-Stationary Dueling Bandits
Aadirupa Saha, Shubham Gupta
ICML 2022 | July 2022
NeuralEF: Deconstructing Kernels by Deep Neural Networks
Zhijie Deng, Jiaxin Shi, Jun Zhu
ICML 2022 | July 2022
Matching Learned Causal Effects of Neural Networks with Domain Priors
Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N Balasubramainan, Amit Sharma
ICML 2022 | July 2022
Gating Dropout: Communication-efficient Regularization for Sparsely Activated Transformers
Rui Liu, Young Jin Kim, Alexandre Muzio, Hany Hassan Awadalla
ICML 2022 | July 2022
Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo, Dongsheng Li, Weining Qian
ICML 2022 | July 2022
Equivariant Diffusion for Molecule Generation in 3D
Emiel Hoogeboom, Victor Garcia Satorras, Clément Vignac, Max Welling
ICML 2022 | July 2022
Data Augmentation as Feature Manipulation
Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar
ICML 2022 | July 2022
Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
ICML 2022 | July 2022
Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness
Adam Foster, Arpi Vezer, Craig Glastonbury, Páidí Creed, Sam Abujudeh, Aaron Sim
ICML 2022 | July 2022
Branching Reinforcement Learning
Yihan Du, Wei Chen
Proceedings of the 39th International Conference on Machine Learning (ICML) | July 2022
Bayesian Nonparametric Learning for Point Processes with Spatial Homogeneity: A Spatial Analysis of NBA Shot Locations
Fan Yin, Jieying Jiao, Guanyu Hu, Jun Yan
ICML 2022 | July 2022
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
ICML 2022 | July 2022
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
ICML 2022 | July 2022
An Intriguing Property of Geophysics Inversion
Yinan Feng, Yinpeng Chen, Shihang Feng, Peng Jin, Zicheng Liu, Youzuo Lin
ICML 2022 | July 2022
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
ICML 2022 | July 2022
Adversarially Trained Actor Critic for Offline Reinforcement Learning
Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal
ICML 2022 | July 2022
Outstanding Paper Runner Up Award
A Framework for Learning to Request Rich and Contextually Useful Information from Humans
Khanh Nguyen, Yonatan Bisk, Hal Daumé III
ICML 2022 | July 2022
RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests
Victor Chernozhukov, Whitney K. Newey, Victor Quintas-Martinez, Vasilis Syrgkanis
ICML 2022 | July 2022
Interactively Learning Preference Constraints in Linear Bandits
David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
ICML 2022 | June 2022
Inductive Biases and Variable Creation in Self-Attention Mechanisms
Benjamin Edelman, Surbhi Goel, Sham Kakade, Cyril Zhang
ICML 2022 | June 2022
Going Deeper into Permutation-Sensitive Graph Neural Networks
Zhongyu Huang, Yingheng Wang, Chaozhuo Li, Huiguang He
ICML 2022 | June 2022
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
ICML 2022 | May 2022
Lie Point Symmetry Data Augmentation for Neural PDE Solvers
Johannes Brandstetter, Max Welling, Daniel E. Worrall
ICML 2022 | February 2022
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
ICML 2022 | January 2022
-
NP-Match: When Neural Processes meet Semi-Supervised Learning
Jianfeng Wang, Thomas Lukasiewicz, Xiaolin Hu, Daniela Massiceti, Vladimir Pavlovic, Alexandros Neophytou
ICML 2022 | July 2022
Lie Point Symmetry Data Augmentation for Neural PDE Solvers
Johannes Brandstetter, Max Welling, Daniel E. Worrall
ICML 2022 | February 2022
-
Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum
Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, Masashi Sugiyama
ICML 2022 | July 2022
-
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
ICML 2022 | January 2022
Publications by Type
-
Contextual Bandits with Large Action Spaces: Made Practical
Yinglun Zhu, Dylan Foster, John Langford, Paul Mineiro
2022 International Conference on Machine Learning | July 2022
A Convergence Theory for SVGD in the Population Limit under Talagrand’s Inequality T1
Adil Salim, Lukang Su, Peter Richtarik
ICML 2022 | July 2022
NP-Match: When Neural Processes meet Semi-Supervised Learning
Jianfeng Wang, Thomas Lukasiewicz, Xiaolin Hu, Daniela Massiceti, Vladimir Pavlovic, Alexandros Neophytou
ICML 2022 | July 2022
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
ICML 2022 | July 2022
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
ICML 2022 | July 2022
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
ICML 2022 | July 2022
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
ICML 2022 | July 2022
Visual Attention Emerges from Recurrent Sparse Reconstruction
Baifeng Shi, Yale Song, Neel Joshi, Xin Wang, Trevor Darrell
ICML 2022 | July 2022
Versatile Dueling Bandits: Best-of-both World Analyses for Learning from Relative Preferences
Aadirupa Saha, Pierre Gaillard
ICML 2022 | July 2022
Universal and data-adaptive algorithms for model selection in linear contextual bandits
Vidya Muthukumar, Akshay Krishnamurthy
ICML 2022 | July 2022
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
ICML 2022 | July 2022
Transformers are Meta-Reinforcement Learners
Luckeciano Carvalho Melo
ICML 2022 | July 2022
Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods
Yi Wan, Harm van Seijen, Ida Momennejad, Sarath Chandar, Janarthanan Rajendran, Ali Rahimi-Kalahroudi
ICML 2022 | July 2022
Supervised Off-Policy Ranking
Yue Jin, Yue Zhang, Tao Qin, Xudong Zhang, Jian Yuan, Houqiang Li, Tie-Yan Liu
ICML 2022 | July 2022
Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models
Viktor Bengs, Aadirupa Saha, Eyke Hüllermeier
ICML 2022 | July 2022
Sparsity in Partially Controllable Linear Systems
Yonathan Efroni, Sham Kakade, Akshay Krishnamurthy, Cyril Zhang
ICML 2022 | July 2022
Simultaneously Learning Stochastic and Adversarial Bandits with General Graph Feedback
Fang Kong, Yichi Zhou, Shuai Li
ICML 2022 | July 2022
Scalable Spike-and-Slab
Niloy Biswas, Lester Mackey, Xiao-Li Meng
ICML 2022 | July 2022
Provable Reinforcement Learning with a Short-Term Memory
Yonathan Efroni, Chi Jin, Akshay Krishnamurthy, Sobhan Miryoosefi
ICML 2022 | July 2022
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Optimization
Alberto Bietti, Chen-Yu Wei, Miro Dudík, John Langford, Steven Wu
ICML 2022 | July 2022
Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback
Darren Lin, Aldo Pacchiano, Yaodong Yu, Michael Jordan
ICML 2022 | July 2022
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
ICML 2022 | July 2022
Non-Stationary Dueling Bandits
Aadirupa Saha, Shubham Gupta
ICML 2022 | July 2022
NeuralEF: Deconstructing Kernels by Deep Neural Networks
Zhijie Deng, Jiaxin Shi, Jun Zhu
ICML 2022 | July 2022
Matching Learned Causal Effects of Neural Networks with Domain Priors
Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N Balasubramainan, Amit Sharma
ICML 2022 | July 2022
Gating Dropout: Communication-efficient Regularization for Sparsely Activated Transformers
Rui Liu, Young Jin Kim, Alexandre Muzio, Hany Hassan Awadalla
ICML 2022 | July 2022
Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo, Dongsheng Li, Weining Qian
ICML 2022 | July 2022
Equivariant Diffusion for Molecule Generation in 3D
Emiel Hoogeboom, Victor Garcia Satorras, Clément Vignac, Max Welling
ICML 2022 | July 2022
Data Augmentation as Feature Manipulation
Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar
ICML 2022 | July 2022
Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
ICML 2022 | July 2022
Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness
Adam Foster, Arpi Vezer, Craig Glastonbury, Páidí Creed, Sam Abujudeh, Aaron Sim
ICML 2022 | July 2022
Branching Reinforcement Learning
Yihan Du, Wei Chen
Proceedings of the 39th International Conference on Machine Learning (ICML) | July 2022
Bayesian Nonparametric Learning for Point Processes with Spatial Homogeneity: A Spatial Analysis of NBA Shot Locations
Fan Yin, Jieying Jiao, Guanyu Hu, Jun Yan
ICML 2022 | July 2022
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
ICML 2022 | July 2022
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
ICML 2022 | July 2022
An Intriguing Property of Geophysics Inversion
Yinan Feng, Yinpeng Chen, Shihang Feng, Peng Jin, Zicheng Liu, Youzuo Lin
ICML 2022 | July 2022
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
ICML 2022 | July 2022
Adversarially Trained Actor Critic for Offline Reinforcement Learning
Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal
ICML 2022 | July 2022
Outstanding Paper Runner Up Award
A Framework for Learning to Request Rich and Contextually Useful Information from Humans
Khanh Nguyen, Yonatan Bisk, Hal Daumé III
ICML 2022 | July 2022
Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum
Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, Masashi Sugiyama
ICML 2022 | July 2022
RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests
Victor Chernozhukov, Whitney K. Newey, Victor Quintas-Martinez, Vasilis Syrgkanis
ICML 2022 | July 2022
Interactively Learning Preference Constraints in Linear Bandits
David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
ICML 2022 | June 2022
Inductive Biases and Variable Creation in Self-Attention Mechanisms
Benjamin Edelman, Surbhi Goel, Sham Kakade, Cyril Zhang
ICML 2022 | June 2022
Going Deeper into Permutation-Sensitive Graph Neural Networks
Zhongyu Huang, Yingheng Wang, Chaozhuo Li, Huiguang He
ICML 2022 | June 2022
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
ICML 2022 | May 2022
Lie Point Symmetry Data Augmentation for Neural PDE Solvers
Johannes Brandstetter, Max Welling, Daniel E. Worrall
ICML 2022 | February 2022
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
ICML 2022 | January 2022