5 citations · 7 across the 14 of their papers we have counts for
17 papers
Ranking Bandits for Carousel Interfaces with Observable Browsing Depth
Takuma Yasuda, Atsuyoshi Nakamura, Dai Hai Nguyen
Carousel interfaces allow a recommender system to directly observe how far a user has browsed. This signal distinguishes displayed but unclicked items from items that were never di…
Selecting k Paths with the Minimum Longest Path Length in the Stochastic Semi-Bandit Setting
Shunsuke Aoki, Atsuyoshi Nakamura
When performing parallel data transmission through a network using multiple paths, it is practically important to minimize the maximum transmission time among the selected paths. T…
Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional Optimization
Dai Hai Nguyen, Hiroshi Mamitsuka, Atsuyoshi Nakamura
We address the optimization problem of simultaneously minimizing multiple objective functionals over a family of probability distributions. This type of Multi-Objective Distributio…
Long-term Detection System for Six Kinds of Abnormal Behavior of the Elderly Living Alone
Kai Tanaka, Mineichi Kudo, Keigo Kimura +1
The proportion of elderly people is increasing worldwide, particularly those living alone in Japan. As elderly people get older, their risks of physical disabilities and health iss…
Pure exploration in multi-armed bandits with low rank structure using oblivious sampler
Yaxiong Liu, Atsuyoshi Nakamura, Kohei Hatano +1
In this paper, we consider the low rank structure of the reward sequence of the pure exploration problems. Firstly, we propose the separated setting in pure exploration problem, wh…
Differentially Private Streaming Data Release under Temporal Correlations via Post-processing
Xuyang Cao, Yang Cao, Primal Pappachan +2
The release of differentially private streaming data has been extensively studied, yet striking a good balance between privacy and utility on temporally correlated data in the stre…
Query Learning Algorithm for Ordered Multi-Terminal Binary Decision Diagrams
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…
Gaussian Process Classification Bandits
Tatsuya Hayashi, Naoki Ito, Koji Tabata +4
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 arm…
Simplification of Forest Classifiers and Regressors
Atsuyoshi Nakamura, Kento Sakurada
We study the problem of sharing as many branching conditions of a given forest classifier or regressor as possible while keeping classification performance. As a constraint for pre…
Slimmable Pruned Neural Networks
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 comput…
Propagation Graph Estimation from Individual's Time Series of Observed States
Tatsuya Hayashi, Atsuyoshi Nakamura
Various things propagate through the medium of individuals. Some individuals follow the others and take the states similar to their states a small number of time steps later. In th…
Minor-embedding heuristics for large-scale annealing processors with sparse hardware graphs of up to 102,400 nodes
Yuya Sugie, Yuki Yoshida, Normann Mertig +7
Minor embedding heuristics have become an indispensable tool for compiling problems in quadratically unconstrained binary optimization (QUBO) into the hardware graphs of quantum an…
A Bad Arm Existence Checking Problem
Koji Tabata, Atsuyoshi Nakamura, Junya Honda +1
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 poss…
Feature selection as Monte-Carlo Search in Growing Single Rooted Directed Acyclic Graph by Best Leaf Identification
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 ot…
Good Arm Identification via Bandit Feedback
Hideaki Kano, Junya Honda, Kentaro Sakamaki +3
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 equ…
On Practical Accuracy of Edit Distance Approximation Algorithms
Hiroyuki Hanada, Mineichi Kudo, Atsuyoshi Nakamura
The edit distance is a basic string similarity measure used in many applications such as text mining, signal processing, bioinformatics, and so on. However, the computational cost…
On-line Learning of Binary Lexical Relations Using Two-dimensional Weighted Majority Algorithms
Naoki Abe, Hang Li, Atsuyoshi Nakamura
We consider the problem of learning a certain type of lexical semantic knowledge that can be expressed as a binary relation between words, such as the so-called sub-categorization…