Bernardo Ávila Pires

According to our database, Bernardo Ávila Pires authored at least 26 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning.

Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo Ávila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana Borsa, Arthur Guez, Will Dabney

CoRR, 2024

Offline Regularised Reinforcement Learning for Large Language Models Alignment.

Pierre Harvey Richemond, Yunhao Tang, Daniel Guo, Daniele Calandriello, Mohammad Gheshlaghi Azar, Rafael Rafailov, Bernardo Ávila Pires, Eugene Tarassov, Lucas Spangher, Will Ellsworth, Aliaksei Severyn, Jonathan Mallinson, Lior Shani, Gil Shamir, Rishabh Joshi, Tianqi Liu, Rémi Munos, Bilal Piot

CoRR, 2024

Understanding the performance gap between online and offline alignment algorithms.

Yunhao Tang, Zhaohan Daniel Guo, Zeyu Zheng, Daniele Calandriello, Yuan Cao, Eugene Tarassov, Rémi Munos, Bernardo Ávila Pires, Michal Valko, Yong Cheng, Will Dabney

CoRR, 2024

Human Alignment of Large Language Models through Online Preference Optimisation.

Daniele Calandriello, Daniel Guo, Rémi Munos, Mark Rowland, Yunhao Tang, Bernardo Ávila Pires, Pierre Harvey Richemond, Charline Le Lan, Michal Valko, Tianqi Liu, Rishabh Joshi, Zeyu Zheng, Bilal Piot

CoRR, 2024

Off-policy Distributional Q(λ): Distributional RL without Importance Sampling.

Yunhao Tang, Mark Rowland, Rémi Munos, Bernardo Ávila Pires, Will Dabney

CoRR, 2024

Generalized Preference Optimization: A Unified Approach to Offline Alignment.

Yunhao Tang, Zhaohan Daniel Guo, Zeyu Zheng, Daniele Calandriello, Rémi Munos, Mark Rowland, Pierre Harvey Richemond, Michal Valko, Bernardo Ávila Pires, Bilal Piot

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Human Alignment of Large Language Models through Online Preference Optimisation.

Daniele Calandriello, Zhaohan Daniel Guo, Rémi Munos, Mark Rowland, Yunhao Tang, Bernardo Ávila Pires, Pierre Harvey Richemond, Charline Le Lan, Michal Valko, Tianqi Liu, Rishabh Joshi, Zeyu Zheng, Bilal Piot

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Hierarchical Reinforcement Learning in Complex 3D Environments.

Bernardo Ávila Pires, Feryal M. P. Behbahani, Hubert Soyer, Kyriacos Nikiforou, Thomas Keck, Satinder Singh

CoRR, 2023

DoMo-AC: Doubly Multi-step Off-policy Actor-Critic Algorithm.

Yunhao Tang, Tadashi Kozuno, Mark Rowland, Anna Harutyunyan, Rémi Munos, Bernardo Ávila Pires, Michal Valko

Proceedings of the International Conference on Machine Learning, 2023

Understanding Self-Predictive Learning for Reinforcement Learning.

Yunhao Tang, Zhaohan Daniel Guo, Pierre Harvey Richemond, Bernardo Ávila Pires, Yash Chandak, Rémi Munos, Mark Rowland, Mohammad Gheshlaghi Azar, Charline Le Lan, Clare Lyle, András György, Shantanu Thakoor, Will Dabney, Bilal Piot, Daniele Calandriello, Michal Valko

Proceedings of the International Conference on Machine Learning, 2023

Understanding Plasticity in Neural Networks.

Clare Lyle, Zeyu Zheng, Evgenii Nikishin, Bernardo Ávila Pires, Razvan Pascanu, Will Dabney

Proceedings of the International Conference on Machine Learning, 2023

2022

The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement Learning.

Yunhao Tang, Rémi Munos, Mark Rowland, Bernardo Ávila Pires, Will Dabney, Marc G. Bellemare

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

BYOL-Explore: Exploration by Bootstrapped Prediction.

Zhaohan Guo, Shantanu Thakoor, Miruna Pislar, Bernardo Ávila Pires, Florent Altché, Corentin Tallec, Alaa Saade, Daniele Calandriello, Jean-Bastien Grill, Yunhao Tang, Michal Valko, Rémi Munos, Mohammad Gheshlaghi Azar, Bilal Piot

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Neural Recursive Belief States in Multi-Agent Reinforcement Learning.

Pol Moreno, Edward Hughes, Kevin R. McKee, Bernardo Ávila Pires, Théophane Weber

CoRR, 2021

Geometric Entropic Exploration.

Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Alaa Saade, Shantanu Thakoor, Bilal Piot, Bernardo Ávila Pires, Michal Valko, Thomas Mesnard, Tor Lattimore, Rémi Munos

CoRR, 2021

2020

Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning.

Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H. Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Ávila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Rémi Munos, Michal Valko

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning.

Zhaohan Daniel Guo, Bernardo Ávila Pires, Bilal Piot, Jean-Bastien Grill, Florent Altché, Rémi Munos, Mohammad Gheshlaghi Azar

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

World Discovery Models.

Mohammad Gheshlaghi Azar, Bilal Piot, Bernardo A. Pires, Jean-Bastien Grill, Florent Altché, Rémi Munos

CoRR, 2019

2018

Neural Predictive Belief Representations.

Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Bernardo A. Pires, Toby Pohlen, Rémi Munos

CoRR, 2018

2016

Multiclass Classification Calibration Functions.

Bernardo Ávila Pires, Csaba Szepesvári

CoRR, 2016

Policy Error Bounds for Model-Based Reinforcement Learning with Factored Linear Models.

Bernardo Ávila Pires, Csaba Szepesvári

CoRR, 2016

Policy Error Bounds for Model-Based Reinforcement Learning with Factored Linear Models.

Bernardo Ávila Pires

Proceedings of the 29th Conference on Learning Theory, 2016

2015

Pathological Effects of Variance on Classification-Based Policy Iteration.

Bernardo Ávila Pires, Csaba Szepesvári

Proceedings of the Learning for General Competency in Video Games, 2015

2014

Pseudo-MDPs and factored linear action models.

Hengshuai Yao, Csaba Szepesvári, Bernardo Ávila Pires, Xinhua Zhang

Proceedings of the 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2014

2013

Cost-sensitive Multiclass Classification Risk Bounds.

Bernardo Ávila Pires, Csaba Szepesvári, Mohammad Ghavamzadeh

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

Statistical linear estimation with penalized estimators: an application to reinforcement learning.

Bernardo Ávila Pires, Csaba Szepesvári

Proceedings of the 29th International Conference on Machine Learning, 2012