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1:07:56
RL Theory Seminar 2024: Audrey Huang (October 22)
0:56:49
RL Theory Seminar 2024: Zakaria Mhammedi (October 15)
1:00:58
Zeyu Jia - Offline Reinforcement Learning: Role of State Aggregation and Trajectory Data
0:33:28
Quanquan Gu - Self-Play Preference Optimization for Language Model Alignment
0:34:35
Simon Du - When are Offline Multi-Agent Games Solvable?
1:09:39
Shipra Agrawal - Optimistic Q-learning for average reward and episodic RL
0:32:15
Sharan Vaswani - Towards Principled, Practical Policy Gradient for Bandits and Tabular MDPs
0:34:15
Niao He - Reinforcement Learning in Mean Field Games: the pitfalls and promises
0:27:57
Philip Amortila - Scalable Online Exploration via Coverability
0:27:18
Philip Amortila - Statistical and Algorithmic Reductions for RL From Rich Observations
0:49:31
Gergely Neu - Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently
0:58:08
Ki Hong - Computationally Efficient Alg for Infinite-Horizon Average Reward RL with Linear MDPs
0:34:51
Ishani Aniruddha Karmarkar - Truncated Variance Reduced Value Iteration
0:31:15
Kevin Jamieson - On the Instance-dependent Sample Complexity of Tabular RL
0:32:00
Dongruo Zhou - Uncertainty-Aware Reward-Free Exploration with General Function Approximation
0:47:58
Brendan O’Donoghue - Efficient exploration in deep RL via utility theory
1:00:29
RL theory seminar 2024: Uri Sherman (May 14)
0:58:07
RL theory seminar 2024: Gene Li (May 7)
0:59:38
RL theory seminar 2024: Sergey Samsonov (Apr 30)
1:01:42
RL theory seminar 2024: Hamish Flynn (Apr 23)
1:03:05
RL theory seminar 2024: Andrew Wagenmaker (Apr 16)
1:00:19
RL theory seminar 2024: Ayush Sekhari (Apr 9)
1:10:27
RL theory seminar 2024: Matthew Zurek (Apr 2)
1:24:32
RL theory seminar 2024: Roberto Cipollone (Mar 26)
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