Microsoft at ICML 2020

Microsoft at ICML 2020

About

Microsoft is proud to be a Gold sponsor of the 37th International Conference on Machine Learning (ICML), as well as Diamond sponsors at the 1st Women in Machine Learning Un-Workshop and Platinum sponsors of the 4th Queer in AI Workshop. We have over 50 papers accepted to the conference, and you can find details of our publications on the Accepted papers and Workshops tabs.

Committee chairs

ICML President: John Langford
ICML Board Members: Hal Daumé III, Hanna Wallach
Program Co-chair: Hal Daumé III

Invited speaker

Tuesday, July 14

05:00 – 06:45 PDT & 16:00 – 17:45 PDT
Doing Some Good with Machine Learning
Invited Speaker: Lester Mackey

Sessions

Tuesday, July 14

07:00 – 07:45 PDT
2nd session: 20:00 – 20:45 PDT
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
Tony Duan, Anand Avati, Daisy Ding, Khanh K. Thai, Sanjay Basu, Andrew Ng, Alejandro Schuler

07:00 – 07:45 PDT
2nd session: 18:00 – 18:45 PDT
Online Learning for Active Cache Synchronization
Andrey Kolobov, Sebastien Bubeck, Julian Zimmert

07:00 – 07:45 PDT
2nd session: 19:00 – 19:45 PDT
Randomized Smoothing of All Shapes and Sizes
Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya Razenshteyn, Jerry Li

07:00 – 07:45 PDT
2nd session: 20:00 – 20:45 PDT
Private Reinforcement Learning with PAC and Regret Guarantees
Giuseppe Vietri, Borja de Balle Pigem, Akshay Krishnamurthy, Steven Wu

07:00 – 07:45 PDT
2nd session: 18:00 – 18:45 PDT
Scalable Nearest Neighbor Search for Optimal Transport
Arturs Backurs, Yihe Dong, Piotr Indyk, Ilya Razenshteyn, Tal Wagner

07:00 – 07:45 PDT
2nd session: 19:00 – 19:45 PDT
Combinatorial Pure Exploration for Dueling Bandit
Wei Chen, Yihan Du, Longbo Huang, Haoyu Zhao

07:00 – 07:45 PDT
2nd session: 19:00 – 19:45 PDT
Distance Metric Learning with Joint Representation Diversification
Xu Chu, Yang Lin, Xiting Wang, Xin Gao, Qi Tong, Hailong Yu, Yasha Wang

07:00 – 07:45 PDT
2nd session: 19:00 – 19:45 PDT
Efficient Domain Generalization via Common-Specific Low-Rank Decomposition
Vihari Piratla, Praneeth Netrapalli, Sunita Sarawagi

07:00 – 07:45 PDT
2nd session: 18:00 – 18:45 PDT
Faster Graph Embeddings via Coarsening
Matthew Fahrbach, Gramoz Goranci, Sushant Sachdeva, Richard Peng, Chi Wang

07:00 – 07:45 PDT
2nd session: 18:00 – 18:45 PDT
What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?
Chi Jin, Praneeth Netrapalli, Michael Jordan

08:00 – 08:45 PDT
2nd session: 19:00 – 19:45 PDT
An end-to-end approach for the verification problem: learning the right distance
Joao Monteiro, Isabela Albuquerque, Jahangir Alam, R Devon Hjelm, Tiago Falk

08:00 – 08:45 PDT
2nd session: 21:00 – 21:45 PDT
Working Memory Graphs
Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew Hausknecht

08:00 – 08:45 PDT
2nd session: 19:00 – 19:45 PDT
Informative Dropout for Robust Representation Learning: A Shape-bias Perspective
Baifeng Shi, Dinghuai Zhang, Qi Dai, Jingdong Wang, Zhanxing Zhu, Yadong Mu

08:00 – 08:45 PDT
2nd session: 21:00 – 21:45 PDT
Near-optimal Sample Complexity Bounds for Learning Latent k−polytopes and applications to Ad-Mixtures
Chiranjib Bhattacharyya, Ravindran Kannan

08:00 – 08:45 PDT
2nd session: 19:00 – 19:45 PDT
Differentially Private Set Union
Pankaj Gulhane, Sivakanth Gopi, Janardhan Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin

08:00 – 08:45 PDT
2nd session: 21:00 – 21:45 PDT
Discount Factor as a Regularizer in Reinforcement Learning
Ron Amit, Kamil Ciosek, Ron Meir

08:00 – 08:45 PDT
2nd session: 21:00 – 21:45 PDT
DROCC: Deep Robust One-Class Classification
Sachin Goyal, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri, Prateek Jain

09:00 – 09:45 PDT
2nd session: 20:00 – 20:45 PDT
Feature Quantization Improves GAN Training
Yang Zhao, Chunyuan Li, Ping Yu, Jianfeng Gao, Changyou Chen

11:00 – 11:45 PDT
2nd session: 22:00 – 22:45 PDT
Optimization and Analysis of the pAp@k Metric for Recommender Systems
Gaurush Hiranandani, Warut Vijitbenjaronk, Sanmi Koyejo, Prateek Jain

11:00 – 11:45 PDT
2nd session: 22:00 – 22:45 PDT
Bandits with Adversarial Scaling
Thodoris Lykouris, Vahab Mirrokni, Renato Leme

13:00 – 13:45 PDT
2nd session: July 15 | 01:00 – 01:45 PDT
GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation
Marc Brockschmidt

18:00 – 18:45 PDT
Online Learning for Active Cache Synchronization
Andrey Kolobov, Sebastien Bubeck, Julian Zimmert

18:00 – 18:45 PDT
Scalable Nearest Neighbor Search for Optimal Transport
Arturs Backurs, Yihe Dong, Piotr Indyk, Ilya Razenshteyn, Tal Wagner

18:00 – 18:45 PDT
Faster Graph Embeddings via Coarsening
Matthew Fahrbach, Gramoz Goranci, Sushant Sachdeva, Richard Peng, Chi Wang

18:00 – 18:45 PDT
What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?
Chi Jin, Praneeth Netrapalli, Michael Jordan

19:00 – 19:45 PDT
Randomized Smoothing of All Shapes and Sizes
Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya Razenshteyn, Jerry Li

19:00 – 19:45 PDT
An end-to-end approach for the verification problem: learning the right distance
Joao Monteiro, Isabela Albuquerque, Jahangir Alam, R Devon Hjelm, Tiago Falk

19:00 – 19:45 PDT
Combinatorial Pure Exploration for Dueling Bandit
Wei Chen, Yihan Du, Longbo Huang, Haoyu Zhao

19:00 – 19:45 PDT
Distance Metric Learning with Joint Representation Diversification
Xu Chu, Yang Lin, Xiting Wang, Xin Gao, Qi Tong, Hailong Yu, Yasha Wang

19:00 – 19:45 PDT
Efficient Domain Generalization via Common-Specific Low-Rank Decomposition
Vihari Piratla, Praneeth Netrapalli, Sunita Sarawagi

19:00 – 19:45 PDT
Informative Dropout for Robust Representation Learning: A Shape-bias Perspective
Baifeng Shi, Dinghuai Zhang, Qi Dai, Jingdong Wang, Zhanxing Zhu, Yadong Mu

19:00 – 19:45 PDT
Differentially Private Set Union
Pankaj Gulhane, Sivakanth Gopi, Janardhan Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin

20:00 – 20:45 PDT
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
Tony Duan, Anand Avati, Daisy Ding, Khanh K. Thai, Sanjay Basu, Andrew Ng, Alejandro Schuler

20:00 – 20:45 PDT
Private Reinforcement Learning with PAC and Regret Guarantees
Giuseppe Vietri, Borja de Balle Pigem, Akshay Krishnamurthy, Steven Wu

20:00 – 20:45 PDT
Feature Quantization Improves GAN Training
Yang Zhao, Chunyuan Li, Ping Yu, Jianfeng Gao, Changyou Chen

21:00 – 21:45 PDT
Working Memory Graphs
Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew Hausknecht

21:00 – 21:45 PDT
Near-optimal Sample Complexity Bounds for Learning Latent k−polytopes and applications to Ad-Mixtures
Chiranjib Bhattacharyya, Ravindran Kannan

21:00 – 21:45 PDT
Discount Factor as a Regularizer in Reinforcement Learning
Ron Amit, Kamil Ciosek, Ron Meir

21:00 – 21:45 PDT
DROCC: Deep Robust One-Class Classification
Sachin Goyal, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri, Prateek Jain

22:00 – 22:45 PDT
Optimization and Analysis of the pAp@k Metric for Recommender Systems
Gaurush Hiranandani, Warut Vijitbenjaronk, Sanmi Koyejo, Prateek Jain

22:00 – 22:45 PDT
Bandits with Adversarial Scaling
Thodoris Lykouris, Vahab Mirrokni, Renato Leme


Wednesday, July 15

01:00 – 01:45 PDT
GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation
Marc Brockschmidt

05:00 – 05:45 PDT
2nd session: 16:00 – 16:45 PDT
Adaptive Estimator Selection for Off-Policy Evaluation
Yi Su, Pavithra Srinath, Akshay Krishnamurthy

05:00 – 05:45 PDT
2nd session: 16:00 – 16:45 PDT
Privately Learning Markov Random Fields
Gautam Kamath, Janardhan Kulkarni, Steven Wu, Huanyu Zhang

08:00 – 08:45 PDT
2nd session: 21:00 – 21:45 PDT
The Non-IID Data Quagmire of Decentralized Machine Learning
Kevin Hsieh, Amar Phanishayee, Onur Mutlu, Phillip Gibbons

08:00 – 08:45 PDT
2nd session: 21:00 – 21:45 PDT
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya Nori

08:00 – 08:45 PDT
2nd session: 21:00 – 21:45 PDT
(Locally) Differentially Private Combinatorial Semi-Bandits
Xiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen, Liwei Wang

08:00 – 08:45 PDT
2nd session: 20:00 – 20:45 PDT
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
Bin Dai, Ziyu Wang, David Wipf

10:00 – 10:45 PDT
2nd session: 21:00 – 21:45 PDT
Single Point Transductive Prediction
Nilesh Tripuraneni, Lester Mackey

10:00 – 10:45 PDT
2nd session: 21:00 – 21:45 PDT
Learning Calibratable Policies using Programmatic Style-Consistency
Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew Hausknecht

11:00 – 11:45 PDT
2nd session: 22:00 – 22:45 PDT
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization
Hadrien Hendrikx, Lin Xiao, Sebastien Bubeck, Francis Bach, Laurent Massoulié

12:00 – 12:45 PDT
2nd session: July 16 | 01:00 – 01:45 PDT
Neuro-Symbolic Visual Reasoning: Disentangling “Visual” from “Reasoning”
Saeed Amizadeh, Hamid Palangi, Oleksandr Polozov, Yichen Huang, Kazuhito Koishida

16:00 – 16:45 PDT
2nd session: July 16 | 03:00 – 03:45 PDT
Optimization from Structured Samples for Coverage Functions
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang

16:00 – 16:45 PDT
Adaptive Estimator Selection for Off-Policy Evaluation
Yi Su, Pavithra Srinath, Akshay Krishnamurthy

16:00 – 16:45 PDT
Privately Learning Markov Random Fields
Gautam Kamath, Janardhan Kulkarni, Steven Wu, Huanyu Zhang

20:00 – 20:45 PDT
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
Bin Dai, Ziyu Wang, David Wipf

21:00 – 21:45 PDT
The Non-IID Data Quagmire of Decentralized Machine Learning
Kevin Hsieh, Amar Phanishayee, Onur Mutlu, Phillip Gibbons

21:00 – 21:45 PDT
Single Point Transductive Prediction
Nilesh Tripuraneni, Lester Mackey

21:00 – 21:45 PDT
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya Nori

21:00 – 21:45 PDT
(Locally) Differentially Private Combinatorial Semi-Bandits
Xiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen, Liwei Wang

21:00 – 21:45 PDT
Learning Calibratable Policies using Programmatic Style-Consistency
Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew Hausknecht

22:00 – 22:45 PDT
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization
Hadrien Hendrikx, Lin Xiao, Sebastien Bubeck, Francis Bach, Laurent Massoulié


Thursday, July 16

01:00 – 01:45 PDT
Neuro-Symbolic Visual Reasoning: Disentangling “Visual” from “Reasoning”
Saeed Amizadeh, Hamid Palangi, Oleksandr Polozov, Yichen Huang, Kazuhito Koishida

03:00 – 03:45 PDT
Optimization from Structured Samples for Coverage Functions
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang

06:00 – 06:45 PDT
2nd session: July 17 | 18:00 – 18:45 PDT
Mapping Natural-language Problems to Formal-language Solutions Using Structured Neural Representations
Kezhen Chen, Qiuyuan Huang, Hamid Palangi, Paul Smolensky, Ken Forbus, Jianfeng Gao

06:00 – 06:45 PDT
2nd session: 17:00 – 17:45 PDT
BINOCULARS for efficient, nonmyopic sequential experimental design
Shali Jiang, Henry Chai, Javier Gonzalez, Roman Garnett

06:00 – 06:45 PDT
2nd session: 18:00 – 18:45 PDT
Black-Box Methods for Restoring Monotonicity
Evangelia Gergatsouli, Brendan Lucier, Christos Tzamos

06:00 – 06:45 PDT
2nd session: 17:00 – 17:45 PDT
CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information
Pengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan, Lawrence Carin

06:00 – 06:45 PDT
2nd session: 17:00 – 17:45 PDT
Neural Datalog Through Time: Informed Temporal Modeling via Logical Specification
Hongyuan Mei, Guanghui Qin, Minjie Xu, Jason Eisner

06:00 – 06:45 PDT
2nd session: 19:00 – 19:45 PDT
Provably Efficient Model-based Policy Adaptation
Yuda Song, Aditi Mavalankar, Wen Sun, Sicun Gao

06:00 – 06:45 PDT
2nd session: 18:00 – 18:45 PDT
Sequence Generation with Mixed Representations
Lijun Wu, Shufang Xie, Yingce Xia, Yang Fan, Jian-Huang Lai, Tao Qin, Tie-Yan Liu

06:00 – 06:45 PDT
2nd session: 17:00 – 17:45 PDT
Reward-Free Exploration for Reinforcement Learning
Chi Jin, Akshay Krishnamurthy, Max Simchowitz, Tiancheng Yu

07:00 – 07:45 PDT
2nd session: 18:00 – 18:45 PDT
No-Regret and Incentive-Compatible Online Learning
Rupert Freeman, David Pennock, Charikleia Podimata, Jennifer Wortman Vaughan

07:00 – 07:45 PDT
2nd session: 18:00 – 18:45 PDT
Graph Optimal Transport for Cross-Domain Alignment
Liqun Chen, Zhe Gan, Yu Cheng, Linjie Li, Lawrence Carin, Jingjing Liu

07:00 – 07:45 PDT
2nd session: 20:00 – 20:45 PDT
Doubly Robust Off-policy Evaluation with Shrinkage
Yi Su, Maria Dimakopoulou, Akshay Krishnamurthy, Miroslav Dudik

07:00 – 07:45 PDT
2nd session: 18:00 – 18:45 PDT
Variance Reduction and Quasi-Newton for Particle-Based Variational Inference Michael Zhu, Chang Liu, Jun Zhu

07:00 – 07:45 PDT
2nd session: 20:00 – 20:45 PDT
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning
Dipendra Misra, Mikael Henaff, Akshay Krishnamurthy, John Langford

08:00 – 08:45 PDT
2nd session: 19:00 – 19:45 PDT
UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training
Hangbo Bao, Li Dong, Furu Wei, Wenhui Wang, Nan Yang, Xiaodong Liu, Yu Wang, Jianfeng Gao, Songhao Piao, Ming Zhou, Hsiao-Wuen Hon

09:00 – 09:45 PDT
2nd session: 23:00 – 23:45 PDT
Bounding the fairness and accuracy of classifiers from population statistics
Sivan Sabato, Elad Yom-Tov

12:00 – 12:45 PDT
2nd session: July 17 | 00:00 – 00:45 PDT
Soft Threshold Weight Reparameterization for Learnable Sparsity
Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham Kakade, Ali Farhadi

17:00 – 17:45 PDT
BINOCULARS for efficient, nonmyopic sequential experimental design
Shali Jiang, Henry Chai, Javier Gonzalez, Roman Garnett

17:00 – 17:45 PDT
CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information
Pengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan, Lawrence Carin

17:00 – 17:45 PDT
Reward-Free Exploration for Reinforcement Learning
Chi Jin, Akshay Krishnamurthy, Max Simchowitz, Tiancheng Yu

18:00 – 18:45 PDT
Mapping Natural-language Problems to Formal-language Solutions Using Structured Neural Representations
Kezhen Chen, Qiuyuan Huang, Hamid Palangi, Paul Smolensky, Ken Forbus, Jianfeng Gao

18:00 – 18:45 PDT
No-Regret and Incentive-Compatible Online Learning
Rupert Freeman, David Pennock, Charikleia Podimata, Jennifer Wortman Vaughan

18:00 – 18:45 PDT
2nd session: July 17 | 04:00 – 04:45 PDT
On Layer Normalization in the Transformer Architecture
Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu

18:00 – 18:45 PDT
Black-Box Methods for Restoring Monotonicity
Evangelia Gergatsouli, Brendan Lucier, Christos Tzamos

18:00 – 18:45 PDT
Graph Optimal Transport for Cross-Domain Alignment
Liqun Chen, Zhe Gan, Yu Cheng, Linjie Li, Lawrence Carin, Jingjing Liu

18:00 – 18:45 PDT
Variance Reduction and Quasi-Newton for Particle-Based Variational Inference Michael Zhu, Chang Liu, Jun Zhu

18:00 – 18:45 PDT
Sequence Generation with Mixed Representations
Lijun Wu, Shufang Xie, Yingce Xia, Yang Fan, Jian-Huang Lai, Tao Qin, Tie-Yan Liu

19:00 – 19:45 PDT
UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training
Hangbo Bao, Li Dong, Furu Wei, Wenhui Wang, Nan Yang, Xiaodong Liu, Yu Wang, Jianfeng Gao, Songhao Piao, Ming Zhou, Hsiao-Wuen Hon

19:00 – 19:45 PDT
Provably Efficient Model-based Policy Adaptation
Yuda Song, Aditi Mavalankar, Wen Sun, Sicun Gao

20:00 – 20:45 PDT
Doubly Robust Off-policy Evaluation with Shrinkage
Yi Su, Maria Dimakopoulou, Akshay Krishnamurthy, Miroslav Dudik

20:00 – 20:45 PDT
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning
Dipendra Misra, Mikael Henaff, Akshay Krishnamurthy, John Langford

23:00 – 23:45 PDT
Bounding the fairness and accuracy of classifiers from population statistics
Sivan Sabato, Elad Yom-Tov


Friday, July 17

00:00 – 00:45 PDT
Soft Threshold Weight Reparameterization for Learnable Sparsity
Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham Kakade, Ali Farhadi

04:00 – 04:45 PDT
On Layer Normalization in the Transformer Architecture
Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu

 

 

Workshops