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2002.03218
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Conservative Exploration in Reinforcement Learning
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
8 February 2020
Evrard Garcelon
Mohammad Ghavamzadeh
A. Lazaric
Matteo Pirotta
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Papers citing
"Conservative Exploration in Reinforcement Learning"
19 / 19 papers shown
Best of Both Worlds: Regret Minimization versus Minimax Play
Adrian Müller
Jon Schneider
Stratis Skoulakis
Luca Viano
Volkan Cevher
OffRL
260
0
0
17 Feb 2025
Conservative Exploration for Policy Optimization via Off-Policy Policy Evaluation
Paul Daoudi
Mathias Formoso
Othman Gaizi
Achraf Azize
Evrard Garcelon
OffRL
233
0
0
24 Dec 2023
Anytime-Competitive Reinforcement Learning with Policy Prior
Neural Information Processing Systems (NeurIPS), 2023
Jianyi Yang
Pengfei Li
Tongxin Li
Adam Wierman
Shaolei Ren
342
3
0
02 Nov 2023
Near-optimal Conservative Exploration in Reinforcement Learning under Episode-wise Constraints
International Conference on Machine Learning (ICML), 2023
Donghao Li
Ruiquan Huang
Cong Shen
Jing Yang
305
4
0
09 Jun 2023
Learning for Edge-Weighted Online Bipartite Matching with Robustness Guarantees
International Conference on Machine Learning (ICML), 2023
Pengfei Li
Jianyi Yang
Shaolei Ren
OffRL
234
7
0
31 May 2023
Leveraging User-Triggered Supervision in Contextual Bandits
Alekh Agarwal
Claudio Gentile
T. V. Marinov
204
0
0
07 Feb 2023
Safe Exploration Incurs Nearly No Additional Sample Complexity for Reward-free RL
International Conference on Learning Representations (ICLR), 2022
Ruiquan Huang
J. Yang
Yingbin Liang
OffRL
326
9
0
28 Jun 2022
Exploration in Deep Reinforcement Learning: A Survey
Information Fusion (Inf. Fusion), 2022
Pawel Ladosz
Lilian Weng
Minwoo Kim
H. Oh
OffRL
391
541
0
02 May 2022
Recent Advances in Reinforcement Learning in Finance
B. Hambly
Renyuan Xu
Huining Yang
OffRL
606
262
0
08 Dec 2021
Explicit Explore, Exploit, or Escape (
E
4
E^4
E
4
): near-optimal safety-constrained reinforcement learning in polynomial time
Machine-mediated learning (ML), 2021
David M. Bossens
Nick Bishop
366
9
0
14 Nov 2021
Uniformly Conservative Exploration in Reinforcement Learning
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Wanqiao Xu
Yecheng Jason Ma
Kan Xu
Hamsa Bastani
Osbert Bastani
OffRL
164
4
0
25 Oct 2021
Bandit Algorithms for Precision Medicine
Yangyi Lu
Ziping Xu
Ambuj Tewari
286
17
0
10 Aug 2021
A Reduction-Based Framework for Conservative Bandits and Reinforcement Learning
Yunchang Yang
Tianhao Wu
Han Zhong
Evrard Garcelon
Matteo Pirotta
A. Lazaric
Liwei Wang
S. Du
OffRL
242
9
0
22 Jun 2021
Safe Reinforcement Learning with Linear Function Approximation
International Conference on Machine Learning (ICML), 2021
Sanae Amani
Christos Thrampoulidis
Lin F. Yang
219
40
0
11 Jun 2021
Online certification of preference-based fairness for personalized recommender systems
AAAI Conference on Artificial Intelligence (AAAI), 2021
Virginie Do
S. Corbett-Davies
Jamal Atif
Nicolas Usunier
FaML
MLAU
331
47
0
29 Apr 2021
Conservative Optimistic Policy Optimization via Multiple Importance Sampling
Achraf Azize
Othman Gaizi
OffRL
113
0
0
04 Mar 2021
A Provably Efficient Sample Collection Strategy for Reinforcement Learning
Neural Information Processing Systems (NeurIPS), 2020
Jean Tarbouriech
Matteo Pirotta
Michal Valko
A. Lazaric
OffRL
316
19
0
13 Jul 2020
Exploration-Exploitation in Constrained MDPs
Yonathan Efroni
Shie Mannor
Matteo Pirotta
432
207
0
04 Mar 2020
Smoothing Policies and Safe Policy Gradients
Machine-mediated learning (ML), 2019
Matteo Papini
Matteo Pirotta
Marcello Restelli
331
36
0
08 May 2019
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