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20092026
most citedOptimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays

70 citations · 245 across the 36 of their papers we have counts for

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Showing 2015Show all

5 papers · 1 filter

stat.ML2015★ 12 cited

Regret Lower Bound and Optimal Algorithm in Finite Stochastic Partial Monitoring

Junpei Komiyama, Junya Honda, Hiroshi Nakagawa

Partial monitoring is a general model for sequential learning with limited feedback formalized as a game between two players. In this game, the learner chooses an action and at the…

cs.IT2015

Almost Instantaneous Fix-to-Variable Length Codes

Hirosuke Yamamoto, Masato Tsuchihashi, Junya Honda

We propose almost instantaneous fixed-to-variable-length (AIFV) codes such that two (resp. ) code trees are used if code symbols are binary (resp. -ary for ), and…

stat.ML2015★ 20 cited

Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem

Junpei Komiyama, Junya Honda, Hisashi Kashima +1

We study the -armed dueling bandit problem, a variation of the standard stochastic bandit problem where the feedback is limited to relative comparisons of a pair of arms. We int…

cs.IT2015★ 4 cited

Exact Asymptotics for the Random Coding Error Probability

Junya Honda

Error probabilities of random codes for memoryless channels are considered in this paper. In the area of communication systems, admissible error probability is very small and it is…

stat.ML2015★ 70 cited

Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays

Junpei Komiyama, Junya Honda, Hiroshi Nakagawa

We discuss a multiple-play multi-armed bandit (MAB) problem in which several arms are selected at each round. Recently, Thompson sampling (TS), a randomized algorithm with a Bayesi…