Model-based reinforcement learning with value-targeted regression A Ayoub, Z Jia, C Szepesvari, M Wang, L Yang International Conference on Machine Learning, 463-474, 2020 | 327 | 2020 |
Randomized exploration in reinforcement learning with general value function approximation H Ishfaq, Q Cui, V Nguyen, A Ayoub, Z Yang, Z Wang, D Precup, L Yang International Conference on Machine Learning, 4607-4616, 2021 | 41 | 2021 |
An elementary proof that Q-learning converges almost surely MT Regehr, A Ayoub arXiv preprint arXiv:2108.02827, 2021 | 9 | 2021 |
Exploration via linearly perturbed loss minimisation D Janz, S Liu, A Ayoub, C Szepesvári International Conference on Artificial Intelligence and Statistics, 721-729, 2024 | 2 | 2024 |
Switching the Loss Reduces the Cost in Batch Reinforcement Learning A Ayoub, K Wang, V Liu, S Robertson, J McInerney, D Liang, N Kallus, ... arXiv preprint arXiv:2403.05385, 2024 | 2 | 2024 |
Managing temporal resolution in continuous value estimation: A fundamental trade-off ZV Zhang, J Kirschner, J Zhang, F Zanini, A Ayoub, M Dehghan, ... Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
Towards Sample Efficient Reinforcement Learning with Function Approximation A Ayoub | | 2021 |
Resmax: An Alternative Soft-Greedy Operator for Reinforcement Learning E Miahi, R MacQueen, A Ayoub, A Masoumzadeh, M White Transactions on Machine Learning Research, 0 | | |