3 citations · 10 across the 9 of their papers we have counts for
5 papers · 1 filter
Contextual Information-Directed Sampling
Botao Hao, Tor Lattimore, Chao Qin
Information-directed sampling (IDS) has recently demonstrated its potential as a data-efficient reinforcement learning algorithm. However, it is still unclear what is the right for…
Information-Directed Selection for Top-Two Algorithms
Wei You, Chao Qin, Zihao Wang +1
We consider the best-k-arm identification problem for multi-armed bandits, where the objective is to select the exact set of k arms with the highest mean rewards by sequentially al…
An Analysis of Ensemble Sampling
Chao Qin, Zheng Wen, Xiuyuan Lu +1
Ensemble sampling serves as a practical approximation to Thompson sampling when maintaining an exact posterior distribution over model parameters is computationally intractable. In…
Adaptive Experimentation in the Presence of Exogenous Nonstationary Variation
Chao Qin, Daniel Russo
We investigate experiments that are designed to select a treatment arm for population deployment. Multi-armed bandit algorithms can enhance efficiency by dynamically allocating mea…
Optimal Best Arm Identification in Two-Armed Bandits with a Fixed Budget under a Small Gap
Masahiro Kato, Kaito Ariu, Masaaki Imaizumi +2
We consider fixed-budget best-arm identification in two-armed Gaussian bandit problems. One of the longstanding open questions is the existence of an optimal strategy under which t…