no code implementations • NeurIPS 2016 • Kentaro Minami, Hitomi Arai, Issei Sato, Hiroshi Nakagawa
The exponential mechanism is a general method to construct a randomized estimator that satisfies $(\varepsilon, 0)$-differential privacy.
no code implementations • 5 May 2016 • Junpei Komiyama, Junya Honda, Hiroshi Nakagawa
We study the K-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.
no code implementations • NeurIPS 2015 • Junpei Komiyama, Junya Honda, Hiroshi Nakagawa
To show the optimality of PM-DMED with respect to the regret bound, we slightly modify the algorithm by introducing a hinge function (PM-DMED-Hinge).
1 code implementation • 8 Jun 2015 • Junpei Komiyama, Junya Honda, Hisashi Kashima, Hiroshi Nakagawa
We study the $K$-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.
1 code implementation • 2 Jun 2015 • Junpei Komiyama, Junya Honda, Hiroshi Nakagawa
Recently, Thompson sampling (TS), a randomized algorithm with a Bayesian spirit, has attracted much attention for its empirically excellent performance, and it is revealed to have an optimal regret bound in the standard single-play MAB problem.
no code implementations • 9 Aug 2014 • Issei Sato, Kenichi Kurihara, Shu Tanaka, Hiroshi Nakagawa, Seiji Miyashita
This paper presents studies on a deterministic annealing algorithm based on quantum annealing for variational Bayes (QAVB) inference, which can be seen as an extension of the simulated annealing for variational Bayes (SAVB) inference.
no code implementations • 19 May 2013 • Issei Sato, Shu Tanaka, Kenichi Kurihara, Seiji Miyashita, Hiroshi Nakagawa
We developed a new quantum annealing (QA) algorithm for Dirichlet process mixture (DPM) models based on the Chinese restaurant process (CRP).
no code implementations • NeurIPS 2010 • Issei Sato, Kenichi Kurihara, Hiroshi Nakagawa
We develop a deterministic single-pass algorithm for latent Dirichlet allocation (LDA) in order to process received documents one at a time and then discard them in an excess text stream.