Beyond the Policy Gradient Theorem for Efficient Policy Updates in Actor-Critic Algorithms
Romain Laroche, Remi Tachet des Combes
AISTATS 2022 | March 2022
March 28, 2022 –
March 30, 2022
Microsoft at AISTATS 2022
Location: Virtual
Publications
Publications
Publications by Year
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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
2022 International Conference on Artificial Intelligence and Statistics | March 2022
Double Control Variates for Gradient Estimation in Discrete Latent Variable Models
Michalis K. Titsias, Jiaxin Shi
2022 International Conference on Artificial Intelligence and Statistics | March 2022
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
2022 International Conference on Artificial Intelligence and Statistics | March 2022
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
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
Exploiting Correlation to Achieve Faster Learning Rates in Low-Rank Preference Bandits
Suprovat Ghoshal, Aadirupa Saha
AISTATS 2022 | February 2022
Investigating the Role of Negatives in Contrastive Representation Learning
Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra
2022 International Conference on Artificial Intelligence and Statistics | February 2022
Learning Inconsistent Preferences with Gaussian Processes
Siu Lun Chau, Javier González, Dino Sejdinovic
International Conference on Artificial Intelligence and Statistics (AISTATS 2022) | January 2022
Meta Learning MDPs with linear transition models
Robert Müller, Aldo Pacchiano
January 2022
-
Towards an Understanding of Default Policies in Multitask Policy Optimization
Ted Moskovitz, Michael Arbel, Jack Parker-Holder, Aldo Pacchiano
AISTATS 2022 | November 2021
Dropout as a Regularizer of Interaction Effects
Benjamin Lengerich, Eric P. Xing, Rich Caruana
October 2021
Learning and Generalization in Overparameterized Normalizing Flows
Kulin Shah, Amit Deshpande, Navin Goyal
AISTATS 2022 | June 2021
Publications by Research Area
-
Beyond the Policy Gradient Theorem for Efficient Policy Updates in Actor-Critic Algorithms
Romain Laroche, Remi Tachet des Combes
AISTATS 2022 | March 2022
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
2022 International Conference on Artificial Intelligence and Statistics | March 2022
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
Double Control Variates for Gradient Estimation in Discrete Latent Variable Models
Michalis K. Titsias, Jiaxin Shi
2022 International Conference on Artificial Intelligence and Statistics | March 2022
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
Exploiting Correlation to Achieve Faster Learning Rates in Low-Rank Preference Bandits
Suprovat Ghoshal, Aadirupa Saha
AISTATS 2022 | February 2022
Investigating the Role of Negatives in Contrastive Representation Learning
Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra
2022 International Conference on Artificial Intelligence and Statistics | February 2022
Learning Inconsistent Preferences with Gaussian Processes
Siu Lun Chau, Javier González, Dino Sejdinovic
International Conference on Artificial Intelligence and Statistics (AISTATS 2022) | January 2022
Meta Learning MDPs with linear transition models
Robert Müller, Aldo Pacchiano
January 2022
Towards an Understanding of Default Policies in Multitask Policy Optimization
Ted Moskovitz, Michael Arbel, Jack Parker-Holder, Aldo Pacchiano
AISTATS 2022 | November 2021
Dropout as a Regularizer of Interaction Effects
Benjamin Lengerich, Eric P. Xing, Rich Caruana
October 2021
Learning and Generalization in Overparameterized Normalizing Flows
Kulin Shah, Amit Deshpande, Navin Goyal
AISTATS 2022 | June 2021
-
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
2022 International Conference on Artificial Intelligence and Statistics | March 2022
-
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
Publications by Type
-
Beyond the Policy Gradient Theorem for Efficient Policy Updates in Actor-Critic Algorithms
Romain Laroche, Remi Tachet des Combes
AISTATS 2022 | March 2022
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
2022 International Conference on Artificial Intelligence and Statistics | March 2022
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
2022 International Conference on Artificial Intelligence and Statistics | March 2022
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
Double Control Variates for Gradient Estimation in Discrete Latent Variable Models
Michalis K. Titsias, Jiaxin Shi
2022 International Conference on Artificial Intelligence and Statistics | March 2022
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
Exploiting Correlation to Achieve Faster Learning Rates in Low-Rank Preference Bandits
Suprovat Ghoshal, Aadirupa Saha
AISTATS 2022 | February 2022
Investigating the Role of Negatives in Contrastive Representation Learning
Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra
2022 International Conference on Artificial Intelligence and Statistics | February 2022
Learning Inconsistent Preferences with Gaussian Processes
Siu Lun Chau, Javier González, Dino Sejdinovic
International Conference on Artificial Intelligence and Statistics (AISTATS 2022) | January 2022
Meta Learning MDPs with linear transition models
Robert Müller, Aldo Pacchiano
January 2022
Towards an Understanding of Default Policies in Multitask Policy Optimization
Ted Moskovitz, Michael Arbel, Jack Parker-Holder, Aldo Pacchiano
AISTATS 2022 | November 2021
Learning and Generalization in Overparameterized Normalizing Flows
Kulin Shah, Amit Deshpande, Navin Goyal
AISTATS 2022 | June 2021
-
Dropout as a Regularizer of Interaction Effects
Benjamin Lengerich, Eric P. Xing, Rich Caruana
October 2021