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A One-Size-Fits-All Solution to Conservative Bandit Problems
v1v2v3v4 (latest)

A One-Size-Fits-All Solution to Conservative Bandit Problems

AAAI Conference on Artificial Intelligence (AAAI), 2020
14 December 2020
Yihan Du
Siwei Wang
Longbo Huang
ArXiv (abs)PDFHTML

Papers citing "A One-Size-Fits-All Solution to Conservative Bandit Problems"

4 / 4 papers shown
Conservative Exploration for Policy Optimization via Off-Policy Policy
  Evaluation
Conservative Exploration for Policy Optimization via Off-Policy Policy Evaluation
Paul Daoudi
Mathias Formoso
Othman Gaizi
Achraf Azize
Evrard Garcelon
OffRL
222
0
0
24 Dec 2023
Anytime-Competitive Reinforcement Learning with Policy Prior
Anytime-Competitive Reinforcement Learning with Policy PriorNeural Information Processing Systems (NeurIPS), 2023
Jianyi Yang
Pengfei Li
Tongxin Li
Adam Wierman
Shaolei Ren
311
3
0
02 Nov 2023
Near-optimal Conservative Exploration in Reinforcement Learning under
  Episode-wise Constraints
Near-optimal Conservative Exploration in Reinforcement Learning under Episode-wise ConstraintsInternational Conference on Machine Learning (ICML), 2023
Donghao Li
Ruiquan Huang
Cong Shen
Jing Yang
259
4
0
09 Jun 2023
A Reduction-Based Framework for Conservative Bandits and Reinforcement
  Learning
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
225
9
0
22 Jun 2021
1
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