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2004.09656
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Tightening Exploration in Upper Confidence Reinforcement Learning
International Conference on Machine Learning (ICML), 2020
20 April 2020
Hippolyte Bourel
Odalric-Ambrym Maillard
M. S. Talebi
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Papers citing
"Tightening Exploration in Upper Confidence Reinforcement Learning"
23 / 23 papers shown
Tail Distribution of Regret in Optimistic Reinforcement Learning
Sajad Khodadadian
Mehrdad Moharrami
129
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The Confusing Instance Principle for Online Linear Quadratic Control
Waris Radji
Odalric-Ambrym Maillard
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177
1
0
22 Oct 2025
Towards Blackwell Optimality: Bellman Optimality Is All You Can Get
Victor Boone
Adrienne Tuynman
131
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0
15 Oct 2025
Q-Learning with Shift-Aware Upper Confidence Bound in Non-Stationary Reinforcement Learning
H. Bui
Felix Parker
Kimia Ghobadi
Anqi Liu
OOD
OffRL
185
0
0
03 Oct 2025
Statistical and Algorithmic Foundations of Reinforcement Learning
Yuejie Chi
Yuxin Chen
Yuting Wei
OffRL
249
2
0
19 Jul 2025
Model Selection for Average Reward RL with Application to Utility Maximization in Repeated Games
Alireza Masoumian
James R. Wright
543
2
0
09 Nov 2024
Learning Infinite-Horizon Average-Reward Linear Mixture MDPs of Bounded Span
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Woojin Chae
Kihyuk Hong
Yufan Zhang
Ambuj Tewari
Dabeen Lee
206
1
0
19 Oct 2024
How to Shrink Confidence Sets for Many Equivalent Discrete Distributions?
Odalric-Ambrym Maillard
M. S. Talebi
164
0
0
22 Jul 2024
Reinforcement Learning and Regret Bounds for Admission Control
International Conference on Machine Learning (ICML), 2024
Lucas Weber
A. Busic
Jiamin Zhu
178
1
0
07 Jun 2024
Achieving Tractable Minimax Optimal Regret in Average Reward MDPs
Victor Boone
Zihan Zhang
226
10
0
03 Jun 2024
Safety through Permissibility: Shield Construction for Fast and Safe Reinforcement Learning
A. Politowicz
Sahisnu Mazumder
Bing-Quan Liu
251
1
0
29 May 2024
Finding good policies in average-reward Markov Decision Processes without prior knowledge
Adrienne Tuynman
Rémy Degenne
Emilie Kaufmann
328
12
0
27 May 2024
Utilizing Maximum Mean Discrepancy Barycenter for Propagating the Uncertainty of Value Functions in Reinforcement Learning
Srinjoy Roy
Swagatam Das
336
0
0
31 Mar 2024
CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption
International Conference on Algorithmic Learning Theory (ALT), 2023
Shubhada Agrawal
Timothée Mathieu
D. Basu
Odalric-Ambrym Maillard
268
4
0
28 Sep 2023
Online Reinforcement Learning in Periodic MDP
IEEE Transactions on Artificial Intelligence (IEEE TAI), 2023
Ayush Aniket
Arpan Chattopadhyay
209
6
0
16 Mar 2023
Reinforcement Learning in a Birth and Death Process: Breaking the Dependence on the State Space
Neural Information Processing Systems (NeurIPS), 2023
Jonatha Anselmi
B. Gaujal
Louis-Sébastien Rebuffi
282
3
0
21 Feb 2023
An Analysis of Model-Based Reinforcement Learning From Abstracted Observations
Rolf A. N. Starre
Marco Loog
E. Congeduti
F. Oliehoek
OffRL
252
3
0
30 Aug 2022
Online Reinforcement Learning for Periodic MDP
Ayush Aniket
Arpan Chattopadhyay
137
0
0
25 Jul 2022
Multiple-Play Stochastic Bandits with Shareable Finite-Capacity Arms
International Conference on Machine Learning (ICML), 2022
Xuchuang Wang
Hong Xie
John C. S. Lui
247
8
0
17 Jun 2022
Reinforcement Learning for Markovian Bandits: Is Posterior Sampling more Scalable than Optimism?
Nicolas Gast
B. Gaujal
K. Khun
335
2
0
16 Jun 2021
UVIP: Model-Free Approach to Evaluate Reinforcement Learning Algorithms
Denis Belomestny
I. Levin
Eric Moulines
A. Naumov
OffRL
284
0
0
05 May 2021
Improved Exploration in Factored Average-Reward MDPs
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
M. S. Talebi
Anders Jonsson
Odalric-Ambrym Maillard
254
9
0
09 Sep 2020
Statistically Robust, Risk-Averse Best Arm Identification in Multi-Armed Bandits
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020
Anmol Kagrecha
Jayakrishnan Nair
Krishna Jagannathan
302
8
0
28 Aug 2020
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