59 citations · 62 across the 7 of their papers we have counts for
3 papers · 1 filter
Thompson Exploration with Best Challenger Rule in Best Arm Identification
Jongyeong Lee, Junya Honda, Masashi Sugiyama
This paper studies the fixed-confidence best arm identification (BAI) problem in the bandit framework in the canonical single-parameter exponential models. For this problem, many p…
Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits
Jongyeong Lee, Junya Honda, Chao-Kai Chiang +1
In the stochastic multi-armed bandit problem, a randomized probability matching policy called Thompson sampling (TS) has shown excellent performance in various reward models. In ad…
The Choice of Noninformative Priors for Thompson Sampling in Multiparameter Bandit Models
Jongyeong Lee, Chao-Kai Chiang, Masashi Sugiyama
Thompson sampling (TS) has been known for its outstanding empirical performance supported by theoretical guarantees across various reward models in the classical stochastic multi-a…