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个人简介
I explore alternative approaches to the classical UCB/Thompson Sampling in the Multi-Armed Bandits problem, with algorithms based on sub-sampling or re-sampling of collected data. By using a few information on the arm’s distribution, this approach allows to design algorithms that can achieve good theoretical guarantees in diverse settings such as the classical K-armed bandit problems, bandits in non-stationary environments, or risk-aware bandits. My research interests also include reinforcement learning, statistics, and machine learning in general.
Interests
Multi-Armed Bandits
Statistics
Machine Learning
Interests
Multi-Armed Bandits
Statistics
Machine Learning
研究兴趣
论文共 12 篇作者统计合作学者相似作者
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FIELD CROPS RESEARCH (2024): 109249
arxiv(2023)
arxiv(2021)
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D-Core
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