research
∙
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...
share
research
∙
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...
research
∙
12/06/2022
Achieving Transparency in Distributed Machine Learning with Explainable Data Collaboration
Transparency of Machine Learning models used for decision support in var...
research
∙
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...
research
∙
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...
research
∙
08/26/2022
Another Use of SMOTE for Interpretable Data Collaboration Analysis
Recently, data collaboration (DC) analysis has been developed for privac...
research
∙
08/16/2022
Collaborative causal inference on distributed data
The development of technologies for causal inference with the privacy pr...
research
∙
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...
research
∙
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...
research
∙
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 ...
research
∙
06/18/2021
LSEC: Large-scale spectral ensemble clustering
Ensemble clustering is a fundamental problem in the machine learning fie...
research
∙
04/30/2021
Divide-and-conquer based Large-Scale Spectral Clustering
Spectral clustering is one of the most popular clustering methods. Howev...
research
∙
01/27/2021
Accuracy and Privacy Evaluations of Collaborative Data Analysis
Distributed data analysis without revealing the individual data has rece...
research
∙
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...
research
∙
11/09/2020
Interpretable collaborative data analysis on distributed data
This paper proposes an interpretable non-model sharing collaborative dat...
research
∙
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...
research
∙
10/16/2019
Multiclass spectral feature scaling method for dimensionality reduction
Irregular features disrupt the desired classification. In this paper, we...
research
∙
02/20/2019
Data collaboration analysis for distributed datasets
In this paper, we propose a data collaboration analysis method for distr...
research
∙
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...
research
∙
05/18/2018
Spectral feature scaling method for supervised dimensionality reduction
Spectral dimensionality reduction methods enable linear separations of c...
research
∙
05/16/2016