Tetsuya Sakurai | DeepAI

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Featured Co-authors

Akira Imakura
19 publications
Claus Aranha
17 publications
Keiichi Morikuni
11 publications
Yifan He
10 publications
Anna Bogdanova
9 publications
Dai Hai Nguyen
7 publications
Hongmin Li
6 publications
Hiroyuki Abe
6 publications
Yukihiko Okada
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Kazumasa Omote
4 publications
Xiucai Ye
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∙ 08/01/2023

Data Collaboration Analysis applied to Compound Datasets and the Introduction of Projection data to Non-IID settings

Given the time and expense associated with bringing a drug to market, nu...

0 Akihiro Mizoguchi, et al. ∙

∙ 07/31/2023

Moreau-Yoshida Variational Transport: A General Framework For Solving Regularized Distributional Optimization Problems

We consider a general optimization problem of minimizing a composite obj...

0 Dai Hai Nguyen, et al. ∙

∙ 12/06/2022

Achieving Transparency in Distributed Machine Learning with Explainable Data Collaboration

Transparency of Machine Learning models used for decision support in var...

0 Anna Bogdanova, et al. ∙

∙ 09/08/2022

Knowledge-Driven Program Synthesis via Adaptive Replacement Mutation and Auto-constructed Subprogram Archives

We introduce Knowledge-Driven Program Synthesis (KDPS) as a variant of t...

0 Yifan He, et al. ∙

∙ 08/31/2022

Non-readily identifiable data collaboration analysis for multiple datasets including personal information

Multi-source data fusion, in which multiple data sources are jointly ana...

0 Akira Imakura, et al. ∙

∙ 08/26/2022

Another Use of SMOTE for Interpretable Data Collaboration Analysis

Recently, data collaboration (DC) analysis has been developed for privac...

0 Akira Imakura, et al. ∙

∙ 08/16/2022

Collaborative causal inference on distributed data

The development of technologies for causal inference with the privacy pr...

0 Yuji Kawamata, et al. ∙

∙ 08/01/2022

A Particle-Based Algorithm for Distributional Optimization on Constrained Domains via Variational Transport and Mirror Descent

We consider the optimization problem of minimizing an objective function...

10 Dai Hai Nguyen, et al. ∙

∙ 12/10/2021

Contour Integral-based Quantum Algorithm for Estimating Matrix Eigenvalue Density

The eigenvalue density of a matrix plays an important role in various ty...

0 Yasunori Futamura, et al. ∙

∙ 09/28/2021

Complex moment-based method with nonlinear transformation for computing large and sparse interior singular triplets

This paper considers computing interior singular triplets corresponding ...

0 Akira Imakura, et al. ∙

∙ 06/18/2021

LSEC: Large-scale spectral ensemble clustering

Ensemble clustering is a fundamental problem in the machine learning fie...

0 Hongmin Li, et al. ∙

∙ 04/30/2021

Divide-and-conquer based Large-Scale Spectral Clustering

Spectral clustering is one of the most popular clustering methods. Howev...

0 Hongmin Li, et al. ∙

∙ 01/27/2021

Accuracy and Privacy Evaluations of Collaborative Data Analysis

Distributed data analysis without revealing the individual data has rece...

0 Akira Imakura, et al. ∙

∙ 11/13/2020

Federated Learning System without Model Sharing through Integration of Dimensional Reduced Data Representations

Dimensionality Reduction is a commonly used element in a machine learnin...

0 Anna Bogdanova, et al. ∙

∙ 11/09/2020

Interpretable collaborative data analysis on distributed data

This paper proposes an interpretable non-model sharing collaborative dat...

0 Akira Imakura, et al. ∙

∙ 10/20/2020

Flexible subspace iteration with moments for an effective contour integration-based eigensolver

Contour integration schemes are a valuable tool for the solution of diff...

0 Sarah Huber, et al. ∙

∙ 10/16/2019

Multiclass spectral feature scaling method for dimensionality reduction

Irregular features disrupt the desired classification. In this paper, we...

0 Momo Matsuda, et al. ∙

∙ 02/20/2019

Data collaboration analysis for distributed datasets

In this paper, we propose a data collaboration analysis method for distr...

0 Akira Imakura, et al. ∙

∙ 12/25/2018

Classification of X-Ray Protein Crystallization Using Deep Convolutional Neural Networks with a Finder Module

Recently, deep convolutional neural networks have shown good results for...

0 Yusei Miura, et al. ∙

∙ 05/18/2018

Spectral feature scaling method for supervised dimensionality reduction

Spectral dimensionality reduction methods enable linear separations of c...

0 Momo Matsuda, et al. ∙

∙ 05/16/2016

Alternating optimization method based on nonnegative matrix factorizations for deep neural networks

The backpropagation algorithm for calculating gradients has been widely ...

0 Tetsuya Sakurai, et al. ∙

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