| Bootstrap your own latent: A new approach to self-supervised learning JB Grill, F Strub, F Altché, C Tallec, PH Richemond, E Buchatskaya, ... arXiv preprint arXiv:2006.07733, 2020 | 186 | 2020 |
| Cost-sensitive multiclass classification risk bounds BA Pires, C Szepesvari, M Ghavamzadeh International Conference on Machine Learning, 1391-1399, 2013 | 44 | 2013 |
| Neural predictive belief representations ZD Guo, MG Azar, B Piot, BA Pires, R Munos arXiv preprint arXiv:1811.06407, 2018 | 26 | 2018 |
| Statistical linear estimation with penalized estimators: an application to reinforcement learning BA Pires, C Szepesvári arXiv preprint arXiv:1206.6444, 2012 | 25 | 2012 |
| Policy error bounds for model-based reinforcement learning with factored linear models BÁ Pires, C Szepesvári Conference on Learning Theory, 121-151, 2016 | 17 | 2016 |
| Bootstrap latent-predictive representations for multitask reinforcement learning ZD Guo, BA Pires, B Piot, JB Grill, F Altché, R Munos, MG Azar International Conference on Machine Learning, 3875-3886, 2020 | 14 | 2020 |
| koray kavukcuoglu, Remi Munos, and Michal Valko. Bootstrap your own latent-a new approach to self-supervised learning JB Grill, F Strub, F Altché, C Tallec, P Richemond, E Buchatskaya, ... Advances in Neural Information Processing Systems 33, 21271-21284, 2020 | 13 | 2020 |
| World discovery models MG Azar, B Piot, BA Pires, JB Grill, F Altché, R Munos arXiv preprint arXiv:1902.07685, 2019 | 13 | 2019 |
| Multiclass classification calibration functions BÁ Pires, C Szepesvári arXiv preprint arXiv:1609.06385, 2016 | 12 | 2016 |
| Neural belief states for partially observed domains P Moreno, J Humplik, G Papamakarios, BA Pires, L Buesing, N Heess, ... NeurIPS 2018 workshop on Reinforcement Learning under Partial Observability, 2018 | 11 | 2018 |
| Pseudo-MDPs and factored linear action models H Yao, C Szepesvári, BA Pires, X Zhang 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement …, 2014 | 11 | 2014 |
| Statistical analysis of l1-penalized linear estimation with applications B Ávila Pires | 6 | 2012 |
| Clause Identification Using Entropy Guided Transformation Learning ER Fernandes, B Pires, CN dos Santos, RL Milidiú Information and Human Language Technology (STIL), 2009 Seventh Brazilian …, 2009 | 5 | 2009 |
| Geometric Entropic Exploration ZD Guo, MG Azar, A Saade, S Thakoor, B Piot, BA Pires, M Valko, ... arXiv preprint arXiv:2101.02055, 2021 | 1 | 2021 |
| Pathological effects of variance on classification-based policy iteration BÁ Pires, C Szepesvári AAAI Workshop: Learning for General Competency in Video Games, 2015 | 1 | 2015 |
| Neural Recursive Belief States in Multi-Agent Reinforcement Learning P Moreno, E Hughes, KR McKee, BA Pires, T Weber arXiv preprint arXiv:2102.02274, 2021 | | 2021 |
| Toward Practical Reinforcement Learning Algorithms: Classification Based Policy Iteration and Model-Based Learning B Ávila Pires | | 2017 |
| Using random projections to estimate condition numbers and solve linear systems CMPUT 501 Project BA Pires | | 2012 |
| CLASSIFICATION CALIBRATION BÁ Pires | | 2012 |
