Off-Policy Actor-Critic T Degris, M White, RS Sutton Twenty-Ninth International Conference on Machine Learning, 2012 | 628 | 2012 |
Meta-learning representations for continual learning K Javed, M White Advances in Neural Information Processing Systems 32, 2019 | 337 | 2019 |
An emphatic approach to the problem of off-policy temporal-difference learning RS Sutton, AR Mahmood, M White Journal of Machine Learning Research 17 (73), 1-29, 2016 | 292 | 2016 |
Supervised autoencoders: Improving generalization performance with unsupervised regularizers L Le, A Patterson, M White Advances in neural information processing systems 31, 2018 | 269 | 2018 |
Convex multi-view subspace learning M White, X Zhang, D Schuurmans, Y Yu Advances in neural information processing systems 25, 2012 | 195 | 2012 |
Maxmin Q-learning: Controlling the Estimation Bias of Q-learning Q Lan, Y Pan, A Fyshe, M White International Conference on Learning Representations, 2020 | 181 | 2020 |
Estimating the class prior and posterior from noisy positives and unlabeled data S Jain, M White, P Radivojac Advances in neural information processing systems 29, 2016 | 133 | 2016 |
Sim2Real in Robotics and Automation: Applications and Challenges S Höfer, K Bekris, A Handa, JC Gamboa, M Mozifian, F Golemo, ... IEEE Transactions on Automation Science and Engineering 18 (2), 398-400, 2021 | 125 | 2021 |
Unifying task specification in reinforcement learning M White International Conference on Machine Learning, 2016 | 112 | 2016 |
Fuzzy Tiling Activations: A Simple Approach to Learning Sparse Representations Online Y Pan, K Banman, M White International Conference on Learning Representations, 2021 | 94* | 2021 |
An off-policy policy gradient theorem using emphatic weightings E Imani, E Graves, M White Advances in Neural Information Processing Systems 31, 2018 | 84 | 2018 |
Recovering true classifier performance in positive-unlabeled learning S Jain, M White, P Radivojac Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 81 | 2017 |
Optimizing for the Future in Non-Stationary MDPs Y Chandak, G Theocharous, S Shankar, S Mahadevan, M White, ... International Conference on Machine Learning, 2020 | 71 | 2020 |
Nonparametric semi-supervised learning of class proportions S Jain, M White, MW Trosset, P Radivojac arXiv preprint arXiv:1601.01944, 2016 | 65 | 2016 |
Improving Regression Performance with Distributional Losses E Imani, M White Advances in Neural Information Processing Systems, 2018 | 58 | 2018 |
The utility of sparse representations for control in reinforcement learning V Liu, R Kumaraswamy, L Le, M White AAAI Conference on Artificial Intelligence, 2019 | 55 | 2019 |
Organizing experience: a deeper look at replay mechanisms for sample-based planning in continuous state domains Y Pan, M Zaheer, A White, A Patterson, M White International Joint Conference on Artificial Intelligence, 2018 | 55 | 2018 |
Relaxed clipping: A global training method for robust regression and classification Y Yu, M Yang, L Xu, M White, D Schuurmans Advances in Neural Information Processing Systems 23, 2011 | 54 | 2011 |
Adapting Behavior via Intrinsic Reward: A Survey and Empirical Study C Linke, NM Ady, M White, T Degris, A White Journal of Artificial Intelligence Research 69, 1287-1332, 2020 | 50 | 2020 |
Gradient Temporal-Difference Learning with Regularized Corrections S Ghiassian, A Patterson, S Garg, D Gupta, A White, M White International Conference on Machine Learning, 3524-3534, 2020 | 48 | 2020 |