| Gradient surgery for multi-task learning T Yu, S Kumar, A Gupta, S Levine, K Hausman, C Finn Advances in Neural Information Processing Systems 33, 5824-5836, 2020 | 983 | 2020 |
| Deepmdp: Learning continuous latent space models for representation learning C Gelada, S Kumar, J Buckman, O Nachum, MG Bellemare International conference on machine learning, 2170-2179, 2019 | 331 | 2019 |
| Dopamine: A research framework for deep reinforcement learning PS Castro, S Moitra, C Gelada, S Kumar, MG Bellemare arXiv preprint arXiv:1812.06110, 2018 | 299 | 2018 |
| Statistics and samples in distributional reinforcement learning M Rowland, R Dadashi, S Kumar, R Munos, MG Bellemare, W Dabney International Conference on Machine Learning, 5528-5536, 2019 | 98 | 2019 |
| One solution is not all you need: Few-shot extrapolation via structured maxent rl S Kumar, A Kumar, S Levine, C Finn Advances in Neural Information Processing Systems 33, 8198-8210, 2020 | 95 | 2020 |
| Federated control with hierarchical multi-agent deep reinforcement learning S Kumar, P Shah, D Hakkani-Tur, L Heck arXiv preprint arXiv:1712.08266, 2017 | 47 | 2017 |
| Learning to compose skills H Sahni, S Kumar, F Tejani, C Isbell arXiv preprint arXiv:1711.11289, 2017 | 40 | 2017 |
| Maintaining Plasticity in Continual Learning via Regenerative Regularization S Kumar, H Marklund, B Van Roy arXiv preprint arXiv:2308.11958, 2023 | 26 | 2023 |
| Characterizing the gap between actor-critic and policy gradient J Wen, S Kumar, R Gummadi, D Schuurmans International Conference on Machine Learning, 11101-11111, 2021 | 18 | 2021 |
| Continual learning as computationally constrained reinforcement learning S Kumar, H Marklund, A Rao, Y Zhu, HJ Jeon, Y Liu, B Van Roy arXiv preprint arXiv:2307.04345, 2023 | 14 | 2023 |
| Multi-task reinforcement learning without interference T Yu, S Kumar, A Gupta, S Levine, K Hausman, C Finn Proc. Optim. Found. Reinforcement Learn. Workshop NeurIPS, 2019 | 6 | 2019 |
| State space decomposition and subgoal creation for transfer in deep reinforcement learning H Sahni, S Kumar, F Tejani, Y Schroecker, C Isbell arXiv preprint arXiv:1705.08997, 2017 | 4 | 2017 |
| Generalized policy updates for policy optimization S Kumar, R Dadashi, Z Ahmed, D Schuurmans, MG Bellemare NeurIPS 2019 Optimization Foundations for Reinforcement Learning Workshop, 2019 | 2 | 2019 |
| The Need for a Big World Simulator: A Scientific Challenge for Continual Learning S Kumar, HJ Jeon, A Lewandowski, B Van Roy Finding the Frame: An RLC Workshop for Examining Conceptual Frameworks, 2024 | | 2024 |
| Satisficing Exploration for Deep Reinforcement Learning D Arumugam, S Kumar, R Gummadi, B Van Roy Finding the Frame: An RLC Workshop for Examining Conceptual Frameworks, 2024 | | 2024 |
| Learning Continually by Spectral Regularization A Lewandowski, S Kumar, D Schuurmans, A György, MC Machado arXiv preprint arXiv:2406.06811, 2024 | | 2024 |
| A Parametric Class of Approximate Gradient Updates for Policy Optimization R Gummadi, S Kumar, J Wen, D Schuurmans International Conference on Machine Learning, 7998-8015, 2022 | | 2022 |
Marc G. BellemareReliant AIVerified email at reliant.ai
