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The Statistical Benefits of Quantile Temporal-Difference Learning for Value Estimation
28 May 2023
Mark Rowland
Yunhao Tang
Clare Lyle
Rémi Munos
Marc G. Bellemare
Will Dabney
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Papers citing
"The Statistical Benefits of Quantile Temporal-Difference Learning for Value Estimation"
10 / 10 papers shown
Title
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL
Jesse Farebrother
Jordi Orbay
Q. Vuong
Adrien Ali Taïga
Yevgen Chebotar
...
Sergey Levine
Pablo Samuel Castro
Aleksandra Faust
Aviral Kumar
Rishabh Agarwal
OffRL
61
59
0
06 Mar 2024
More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning
Kaiwen Wang
Owen Oertell
Alekh Agarwal
Nathan Kallus
Wen Sun
OffRL
88
12
0
11 Feb 2024
Beyond Average Return in Markov Decision Processes
Alexandre Marthe
Aurélien Garivier
Claire Vernade
43
6
0
31 Oct 2023
Robust Offline Reinforcement learning with Heavy-Tailed Rewards
Jin Zhu
Runzhe Wan
Zhengling Qi
Shuang Luo
C. Shi
OffRL
59
0
0
28 Oct 2023
Variance Control for Distributional Reinforcement Learning
Qi Kuang
Zhoufan Zhu
Liwen Zhang
Fan Zhou
OffRL
35
3
0
30 Jul 2023
One-Step Distributional Reinforcement Learning
Mastane Achab
Réda Alami
Y. A. D. Djilali
Kirill Fedyanin
Eric Moulines
OOD
OffRL
41
3
0
27 Apr 2023
An Analysis of Quantile Temporal-Difference Learning
Mark Rowland
Rémi Munos
M. G. Azar
Yunhao Tang
Georg Ostrovski
Anna Harutyunyan
K. Tuyls
Marc G. Bellemare
Will Dabney
31
23
0
11 Jan 2023
How Does Value Distribution in Distributional Reinforcement Learning Help Optimization?
Ke Sun
Bei Jiang
Linglong Kong
29
4
0
29 Sep 2022
Distributional Reinforcement Learning by Sinkhorn Divergence
Ke Sun
Yingnan Zhao
Wulong Liu
Bei Jiang
Linglong Kong
40
0
0
01 Feb 2022
The Benefits of Being Categorical Distributional: Uncertainty-aware Regularized Exploration in Reinforcement Learning
Ke Sun
Yingnan Zhao
Enze Shi
Yafei Wang
Xiaodong Yan
Bei Jiang
Linglong Kong
OOD
OffRL
UQCV
39
2
0
07 Oct 2021
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