no code implementations • 28 Jun 2023 • Yaxiong Liu, Atsuyoshi Nakamura, Kohei Hatano, Eiji Takimoto

Then, we show the lower bound to the pure exploration in multi-armed bandits with low rank sequence.

no code implementations • 3 Mar 2023 • Atsuyoshi Nakamura

We propose a query learning algorithm for ordered multi-terminal binary decision diagrams (OMTBDDs) using at most n equivalence and 2n(l\lcei\log_2 m\rceil+ 3n) membership queries by extending the algorithm for ordered binary decision diagrams (OBDDs).

no code implementations • 26 Dec 2022 • Tatsuya Hayashi, Naoki Ito, Koji Tabata, Atsuyoshi Nakamura, Katsumasa Fujita, Yoshinori Harada, Tamiki Komatsuzaki

Classification bandits are multi-armed bandit problems whose task is to classify a given set of arms into either positive or negative class depending on whether the rate of the arms with the expected reward of at least h is not less than w for given thresholds h and w. We study a special classification bandit problem in which arms correspond to points x in d-dimensional real space with expected rewards f(x) which are generated according to a Gaussian process prior.

no code implementations • 14 Dec 2022 • Atsuyoshi Nakamura, Kento Sakurada

The constraint is relaxed later to promote further sharing of branching conditions by allowing decision path change of a certain ratio of the given feature vectors or allowing a certain number of non-intersected constraint-satisfying intervals.

1 code implementation • 7 Dec 2022 • Hideaki Kuratsu, Atsuyoshi Nakamura

Slimmable Neural Networks (S-Net) is a novel network which enabled to select one of the predefined proportions of channels (sub-network) dynamically depending on the current computational resource availability.

no code implementations • 11 May 2020 • Tatsuya Hayashi, Atsuyoshi Nakamura

Various things propagate through the medium of individuals.

no code implementations • 31 Jan 2019 • Koji Tabata, Atsuyoshi Nakamura, Junya Honda, Tamiki Komatsuzaki

We study a bad arm existing checking problem in which a player's task is to judge whether a positive arm exists or not among given K arms by drawing as small number of arms as possible.

1 code implementation • 19 Nov 2018 • Aurelien Pelissier, Atsuyoshi Nakamura, Koji Tabata

Monte Carlo tree search (MCTS) has received considerable interest due to its spectacular success in the difficult problem of computer Go and also proved beneficial in a range of other domains.

no code implementations • 17 Oct 2017 • Hideaki Kano, Junya Honda, Kentaro Sakamaki, Kentaro Matsuura, Atsuyoshi Nakamura, Masashi Sugiyama

We consider a novel stochastic multi-armed bandit problem called {\em good arm identification} (GAI), where a good arm is defined as an arm with expected reward greater than or equal to a given threshold.

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