| Data-efficient off-policy policy evaluation for reinforcement learning P Thomas, E Brunskill International conference on machine learning, 2139-2148, 2016 | 875 | 2016 |
| Value function approximation in reinforcement learning using the Fourier basis G Konidaris, S Osentoski, P Thomas Proceedings of the AAAI conference on artificial intelligence 25 (1), 380-385, 2011 | 578 | 2011 |
| High-confidence off-policy evaluation P Thomas, G Theocharous, M Ghavamzadeh Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 387 | 2015 |
| Learning action representations for reinforcement learning Y Chandak, G Theocharous, J Kostas, S Jordan, P Thomas International conference on machine learning, 941-950, 2019 | 254 | 2019 |
| High confidence policy improvement P Thomas, G Theocharous, M Ghavamzadeh International Conference on Machine Learning, 2380-2388, 2015 | 251 | 2015 |
| Preventing undesirable behavior of intelligent machines P Thomas, B Castro da Silva, A Barto, S Giguere, Y Brun, E Brunskill Science 366 (6468), 999-1004, 2019 | 232 | 2019 |
| Ad recommendation systems for life-time value optimization G Theocharous, PS Thomas, M Ghavamzadeh Proceedings of the 24th international conference on world wide web, 1305-1310, 2015 | 225 | 2015 |
| Increasing the action gap: New operators for reinforcement learning MG Bellemare, G Ostrovski, A Guez, P Thomas, R Munos Proceedings of the AAAI conference on artificial intelligence 30 (1), 2016 | 191 | 2016 |
| Bias in natural actor-critic algorithms P Thomas International conference on machine learning, 441-448, 2014 | 185 | 2014 |
| Safe reinforcement learning PS Thomas University of Massachusetts Libraries, 2015 | 136 | 2015 |
| Evaluating the performance of reinforcement learning algorithms S Jordan, Y Chandak, D Cohen, M Zhang, P Thomas International Conference on Machine Learning, 4962-4973, 2020 | 135 | 2020 |
| Is the policy gradient a gradient? C Nota, PS Thomas arXiv preprint arXiv:1906.07073, 2019 | 99 | 2019 |
| Optimization and evaluation of a proportional derivative controller for planar arm movement KM Jagodnik, AJ van den Bogert Journal of Biomechanics 43 (6), 1086-1091, 2010 | 94 | 2010 |
| Optimizing for the future in non-stationary mdps Y Chandak, G Theocharous, S Shankar, M White, S Mahadevan, ... International Conference on Machine Learning, 1414-1425, 2020 | 85 | 2020 |
| Policy gradient methods for reinforcement learning with function approximation and action-dependent baselines PS Thomas, E Brunskill arXiv preprint arXiv:1706.06643, 2017 | 81 | 2017 |
| Training an actor-critic reinforcement learning controller for arm movement using human-generated rewards KM Jagodnik, PS Thomas, AJ van den Bogert, MS Branicky, RF Kirsch IEEE Transactions on Neural Systems and Rehabilitation Engineering 25 (10 …, 2017 | 80 | 2017 |
| Proximal reinforcement learning: A new theory of sequential decision making in primal-dual spaces S Mahadevan, B Liu, P Thomas, W Dabney, S Giguere, N Jacek, I Gemp, ... arXiv preprint arXiv:1405.6757, 2014 | 75 | 2014 |
| Fairness guarantees under demographic shift S Giguere, B Metevier, BC da Silva, Y Brun, PS Thomas, S Niekum International Conference on Learning Representations, 2022 | 74 | 2022 |
| Universal off-policy evaluation Y Chandak, S Niekum, B da Silva, E Learned-Miller, E Brunskill, ... Advances in Neural Information Processing Systems 34, 27475-27490, 2021 | 72 | 2021 |
| Offline contextual bandits with high probability fairness guarantees B Metevier, S Giguere, S Brockman, A Kobren, Y Brun, E Brunskill, ... Advances in neural information processing systems 32, 2019 | 72 | 2019 |
Georgios TheocharousAdobe ResearchVerified email at adobe.com
