Saurabh Kumar
Saurabh Kumar
在 stanford.edu 的电子邮件经过验证
标题
引用次数
引用次数
年份
Dopamine: A research framework for deep reinforcement learning
PS Castro, S Moitra, C Gelada, S Kumar, MG Bellemare
arXiv preprint arXiv:1812.06110, 2018
1412018
Gradient surgery for multi-task learning
T Yu, S Kumar, A Gupta, S Levine, K Hausman, C Finn
arXiv preprint arXiv:2001.06782, 2020
912020
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
842019
Federated control with hierarchical multi-agent deep reinforcement learning
S Kumar, P Shah, D Hakkani-Tur, L Heck
arXiv preprint arXiv:1712.08266, 2017
292017
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
262019
Learning to compose skills
H Sahni, S Kumar, F Tejani, C Isbell
arXiv preprint arXiv:1711.11289, 2017
252017
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, 2020
52020
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
32017
Generalized Policy Updates for Policy Optimization
S Kumar, Z Ahmed, R Dadashi, D Schuurmans, MG Bellemare
NeurIPS 2019 Optimization Foundations for Reinforcement Learning Workshop, 2019
12019
Characterizing the Gap Between Actor-Critic and Policy Gradient
J Wen, S Kumar, R Gummadi, D Schuurmans
arXiv preprint arXiv:2106.06932, 2021
2021
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