6 citations · 9 across the 4 of their papers we have counts for
4 papers
Variance-Dependent Best Arm Identification
Pinyan Lu, Chao Tao, Xiaojin Zhang
We study the problem of identifying the best arm in a stochastic multi-armed bandit game. Given a set of arms indexed from to , each arm is associated with an unknow…
Near-Optimal MNL Bandits Under Risk Criteria
Guangyu Xi, Chao Tao, Yuan Zhou
We study MNL bandits, which is a variant of the traditional multi-armed bandit problem, under risk criteria. Unlike the ordinary expected revenue, risk criteria are more general go…
Thresholding Bandit with Optimal Aggregate Regret
Chao Tao, Saùl Blanco, Jian Peng +1
We consider the thresholding bandit problem, whose goal is to find arms of mean rewards above a given threshold , with a fixed budget of trials. We introduce LSA, a new, sim…
Collaborative Learning with Limited Interaction: Tight Bounds for Distributed Exploration in Multi-Armed Bandits
Chao Tao, Qin Zhang, Yuan Zhou
Best arm identification (or, pure exploration) in multi-armed bandits is a fundamental problem in machine learning. In this paper we study the distributed version of this problem w…