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Titel
Zitiert von
Zitiert von
Jahr
Data-Efficient Hierarchical Reinforcement Learning
O Nachum, S Gu, H Lee, S Levine
Advances in Neural Information Processing Systems, 2018
2682018
Learning to remember rare events
Ł Kaiser, O Nachum, A Roy, S Bengio
International Conference for Learning Representations, 2017
2532017
Bridging the gap between value and policy based reinforcement learning
O Nachum, M Norouzi, K Xu, D Schuurmans
arXiv preprint arXiv:1702.08892, 2017
2232017
Morphnet: Fast & simple resource-constrained structure learning of deep networks
A Gordon, E Eban, O Nachum, B Chen, H Wu, TJ Yang, E Choi
Proceedings of the IEEE conference on computer vision and pattern …, 2018
1972018
A Lyapunov-based Approach to Safe Reinforcement Learning
Y Chow, O Nachum, E Duenez-Guzman, M Ghavamzadeh
Advances in Neural Information Processing Systems, 2018
1462018
Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods
D Quillen, E Jang, O Nachum, C Finn, J Ibarz, S Levine
IEEE International Conference on Robotics and Automation, 2018
1062018
Near-optimal representation learning for hierarchical reinforcement learning
O Nachum, S Gu, H Lee, S Levine
arXiv preprint arXiv:1810.01257, 2018
682018
Trust-pcl: An off-policy trust region method for continuous control
O Nachum, M Norouzi, K Xu, D Schuurmans
International Conference for Learning Representations, 2018
682018
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
662019
Dualdice: Behavior-agnostic estimation of discounted stationary distribution corrections
O Nachum, Y Chow, B Dai, L Li
arXiv preprint arXiv:1906.04733, 2019
652019
Behavior regularized offline reinforcement learning
Y Wu, G Tucker, O Nachum
arXiv preprint arXiv:1911.11361, 2019
592019
Identifying and correcting label bias in machine learning
H Jiang, O Nachum
International Conference on Artificial Intelligence and Statistics, 702-712, 2020
472020
Lyapunov-based safe policy optimization for continuous control
Y Chow, O Nachum, A Faust, E Duenez-Guzman, M Ghavamzadeh
arXiv preprint arXiv:1901.10031, 2019
462019
D4rl: Datasets for deep data-driven reinforcement learning
J Fu, A Kumar, O Nachum, G Tucker, S Levine
arXiv preprint arXiv:2004.07219, 2020
452020
Algaedice: Policy gradient from arbitrary experience
O Nachum, B Dai, I Kostrikov, Y Chow, L Li, D Schuurmans
arXiv preprint arXiv:1912.02074, 2019
342019
Improving policy gradient by exploring under-appreciated rewards
O Nachum, M Norouzi, D Schuurmans
International Conference for Learning Representations, 2017
282017
Why does hierarchy (sometimes) work so well in reinforcement learning?
O Nachum, H Tang, X Lu, S Gu, H Lee, S Levine
arXiv preprint arXiv:1909.10618, 2019
222019
Path consistency learning in tsallis entropy regularized mdps
Y Chow, O Nachum, M Ghavamzadeh
International Conference on Machine Learning, 979-988, 2018
21*2018
Multi-agent manipulation via locomotion using hierarchical sim2real
O Nachum, M Ahn, H Ponte, S Gu, V Kumar
arXiv preprint arXiv:1908.05224, 2019
182019
Reinforcement learning via fenchel-rockafellar duality
O Nachum, B Dai
arXiv preprint arXiv:2001.01866, 2020
172020
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