Search Results for author: Atsuyoshi Nakamura

Found 9 papers, 2 papers with code

Query Learning Algorithm for Ordered Multi-Terminal Binary Decision Diagrams

no code implementations3 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).

Gaussian Process Classification Bandits

no code implementations26 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.

Active Learning Classification

Simplification of Forest Classifiers and Regressors

no code implementations14 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.

Slimmable Pruned Neural Networks

1 code implementation7 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.

A Bad Arm Existence Checking Problem

no code implementations31 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.

Feature selection as Monte-Carlo Search in Growing Single Rooted Directed Acyclic Graph by Best Leaf Identification

1 code implementation19 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.

feature selection

Good Arm Identification via Bandit Feedback

no code implementations17 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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