background pattern in hues of purple and blue

March 28, 2022 – March 30, 2022

Microsoft at AISTATS 2022

Location: Virtual

Publications

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- Beyond the Policy Gradient Theorem for Efficient Policy Updates in Actor-Critic Algorithms
  
  Romain Laroche, Remi Tachet des Combes
  
  AISTATS 2022 | March 2022
  
  Publication Project
- A general class of surrogate functions for stable and efficient reinforcement learning
  
  Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Müller, Shivam Garg, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux
  
  International Conference on Artificial Intelligence and Statistics | March 2022
  
  Publication
- Double Control Variates for Gradient Estimation in Discrete Latent Variable Models
  
  Michalis K. Titsias, Jiaxin Shi
  
  International Conference on Artificial Intelligence and Statistics | March 2022
  
  Publication
- On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging
  
  Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan
  
  International Conference on Artificial Intelligence and Statistics | March 2022
  
  Publication
- Online Competitive Influence Maximization
  
  Jinhang Zuo, Xutong Liu, Carlee Joe-Wong, John C.S. Lui, Wei Chen
  
  Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS) | March 2022
  
  PDF
- Predicting the impact of treatments over time with uncertainty aware neural differential equations
  
  Edward De Brouwer, Javier González, Stephanie Hyland
  
  International Conference on Artificial Intelligence and Statistics (AISTATS 2022) | February 2022
  
  Publication
- Exploiting Correlation to Achieve Faster Learning Rates in Low-Rank Preference Bandits
  
  Suprovat Ghoshal, Aadirupa Saha
  
  AISTATS 2022 | February 2022
  
  Publication
- Investigating the Role of Negatives in Contrastive Representation Learning
  
  Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra
  
  International Conference on Artificial Intelligence and Statistics | February 2022
  
  Publication
- Learning Inconsistent Preferences with Gaussian Processes
  
  Siu Lun Chau, Javier González, Dino Sejdinovic
  
  International Conference on Artificial Intelligence and Statistics (AISTATS 2022) | January 2022
  
  PDF
- Meta Learning MDPs with linear transition models
  
  Robert Müller, Aldo Pacchiano
  
  January 2022
  
  Publication
- Towards an Understanding of Default Policies in Multitask Policy Optimization
  
  Ted Moskovitz, Michael Arbel, Jack Parker-Holder, Aldo Pacchiano
  
  AISTATS 2022 | November 2021
  
  Publication
- Dropout as a Regularizer of Interaction Effects
  
  Benjamin Lengerich, Eric P. Xing, Rich Caruana
  
  October 2021
  
  arXiv | October 2021
  
  Publication
- Learning and Generalization in Overparameterized Normalizing Flows
  
  Kulin Shah, Amit Deshpande, Navin Goyal
  
  AISTATS 2022 | June 2021
  
  Publication

- Beyond the Policy Gradient Theorem for Efficient Policy Updates in Actor-Critic Algorithms
  
  Romain Laroche, Remi Tachet des Combes
  
  AISTATS 2022 | March 2022
  
  Publication Project
- A general class of surrogate functions for stable and efficient reinforcement learning
  
  Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Müller, Shivam Garg, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux
  
  International Conference on Artificial Intelligence and Statistics | March 2022
  
  Publication
- Online Competitive Influence Maximization
  
  Jinhang Zuo, Xutong Liu, Carlee Joe-Wong, John C.S. Lui, Wei Chen
  
  Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS) | March 2022
  
  PDF
- Double Control Variates for Gradient Estimation in Discrete Latent Variable Models
  
  Michalis K. Titsias, Jiaxin Shi
  
  International Conference on Artificial Intelligence and Statistics | March 2022
  
  Publication
- Predicting the impact of treatments over time with uncertainty aware neural differential equations
  
  Edward De Brouwer, Javier González, Stephanie Hyland
  
  International Conference on Artificial Intelligence and Statistics (AISTATS 2022) | February 2022
  
  Publication
- Exploiting Correlation to Achieve Faster Learning Rates in Low-Rank Preference Bandits
  
  Suprovat Ghoshal, Aadirupa Saha
  
  AISTATS 2022 | February 2022
  
  Publication
- Investigating the Role of Negatives in Contrastive Representation Learning
  
  Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra
  
  International Conference on Artificial Intelligence and Statistics | February 2022
  
  Publication
- Learning Inconsistent Preferences with Gaussian Processes
  
  Siu Lun Chau, Javier González, Dino Sejdinovic
  
  International Conference on Artificial Intelligence and Statistics (AISTATS 2022) | January 2022
  
  PDF
- Meta Learning MDPs with linear transition models
  
  Robert Müller, Aldo Pacchiano
  
  January 2022
  
  Publication
- Towards an Understanding of Default Policies in Multitask Policy Optimization
  
  Ted Moskovitz, Michael Arbel, Jack Parker-Holder, Aldo Pacchiano
  
  AISTATS 2022 | November 2021
  
  Publication
- Dropout as a Regularizer of Interaction Effects
  
  Benjamin Lengerich, Eric P. Xing, Rich Caruana
  
  October 2021
  
  arXiv | October 2021
  
  Publication
- Learning and Generalization in Overparameterized Normalizing Flows
  
  Kulin Shah, Amit Deshpande, Navin Goyal
  
  AISTATS 2022 | June 2021
  
  Publication
- On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging
  
  Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan
  
  International Conference on Artificial Intelligence and Statistics | March 2022
  
  Publication
- Online Competitive Influence Maximization
  
  Jinhang Zuo, Xutong Liu, Carlee Joe-Wong, John C.S. Lui, Wei Chen
  
  Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS) | March 2022
  
  PDF

- Beyond the Policy Gradient Theorem for Efficient Policy Updates in Actor-Critic Algorithms
  
  Romain Laroche, Remi Tachet des Combes
  
  AISTATS 2022 | March 2022
  
  Publication Project
- On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging
  
  Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan
  
  International Conference on Artificial Intelligence and Statistics | March 2022
  
  Publication
- A general class of surrogate functions for stable and efficient reinforcement learning
  
  Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Müller, Shivam Garg, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux
  
  International Conference on Artificial Intelligence and Statistics | March 2022
  
  Publication
- Online Competitive Influence Maximization
  
  Jinhang Zuo, Xutong Liu, Carlee Joe-Wong, John C.S. Lui, Wei Chen
  
  Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS) | March 2022
  
  PDF
- Double Control Variates for Gradient Estimation in Discrete Latent Variable Models
  
  Michalis K. Titsias, Jiaxin Shi
  
  International Conference on Artificial Intelligence and Statistics | March 2022
  
  Publication
- Predicting the impact of treatments over time with uncertainty aware neural differential equations
  
  Edward De Brouwer, Javier González, Stephanie Hyland
  
  International Conference on Artificial Intelligence and Statistics (AISTATS 2022) | February 2022
  
  Publication
- Exploiting Correlation to Achieve Faster Learning Rates in Low-Rank Preference Bandits
  
  Suprovat Ghoshal, Aadirupa Saha
  
  AISTATS 2022 | February 2022
  
  Publication
- Investigating the Role of Negatives in Contrastive Representation Learning
  
  Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra
  
  International Conference on Artificial Intelligence and Statistics | February 2022
  
  Publication
- Learning Inconsistent Preferences with Gaussian Processes
  
  Siu Lun Chau, Javier González, Dino Sejdinovic
  
  International Conference on Artificial Intelligence and Statistics (AISTATS 2022) | January 2022
  
  PDF
- Meta Learning MDPs with linear transition models
  
  Robert Müller, Aldo Pacchiano
  
  January 2022
  
  Publication
- Towards an Understanding of Default Policies in Multitask Policy Optimization
  
  Ted Moskovitz, Michael Arbel, Jack Parker-Holder, Aldo Pacchiano
  
  AISTATS 2022 | November 2021
  
  Publication
- Learning and Generalization in Overparameterized Normalizing Flows
  
  Kulin Shah, Amit Deshpande, Navin Goyal
  
  AISTATS 2022 | June 2021
  
  Publication
- Dropout as a Regularizer of Interaction Effects
  
  Benjamin Lengerich, Eric P. Xing, Rich Caruana
  
  October 2021
  
  arXiv | October 2021
  
  Publication

Microsoft at AISTATS 2022

Publications

Beyond the Policy Gradient Theorem for Efficient Policy Updates in Actor-Critic Algorithms

A general class of surrogate functions for stable and efficient reinforcement learning

Double Control Variates for Gradient Estimation in Discrete Latent Variable Models

On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging

Online Competitive Influence Maximization

Predicting the impact of treatments over time with uncertainty aware neural differential equations

Exploiting Correlation to Achieve Faster Learning Rates in Low-Rank Preference Bandits

Investigating the Role of Negatives in Contrastive Representation Learning

Learning Inconsistent Preferences with Gaussian Processes

Meta Learning MDPs with linear transition models

Towards an Understanding of Default Policies in Multitask Policy Optimization

Dropout as a Regularizer of Interaction Effects

Learning and Generalization in Overparameterized Normalizing Flows

Beyond the Policy Gradient Theorem for Efficient Policy Updates in Actor-Critic Algorithms

A general class of surrogate functions for stable and efficient reinforcement learning

Online Competitive Influence Maximization

Double Control Variates for Gradient Estimation in Discrete Latent Variable Models

Predicting the impact of treatments over time with uncertainty aware neural differential equations

Exploiting Correlation to Achieve Faster Learning Rates in Low-Rank Preference Bandits

Investigating the Role of Negatives in Contrastive Representation Learning

Learning Inconsistent Preferences with Gaussian Processes

Meta Learning MDPs with linear transition models

Towards an Understanding of Default Policies in Multitask Policy Optimization

Dropout as a Regularizer of Interaction Effects

Learning and Generalization in Overparameterized Normalizing Flows

On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging

Online Competitive Influence Maximization

Beyond the Policy Gradient Theorem for Efficient Policy Updates in Actor-Critic Algorithms

On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging

A general class of surrogate functions for stable and efficient reinforcement learning

Online Competitive Influence Maximization

Double Control Variates for Gradient Estimation in Discrete Latent Variable Models

Predicting the impact of treatments over time with uncertainty aware neural differential equations

Exploiting Correlation to Achieve Faster Learning Rates in Low-Rank Preference Bandits

Investigating the Role of Negatives in Contrastive Representation Learning

Learning Inconsistent Preferences with Gaussian Processes

Meta Learning MDPs with linear transition models

Towards an Understanding of Default Policies in Multitask Policy Optimization

Learning and Generalization in Overparameterized Normalizing Flows

Dropout as a Regularizer of Interaction Effects