works on
co-clustering 1hypothesis testing 1multivariate regression 1non-negative matrix factorization 1reduced-rank regression 1

From the 1 of 4 linked papers with an AI index.

collaborators

4 papers

stat.ME2026

Co-clustering of Response and Covariate Variables by Tri-Factorizing Their Non-negative Regression Coefficient Matrix

Kenichi Satoh, Yomei Tokuda

The paper introduces a tri-factorization of a non‑negative regression coefficient matrix to simultaneously cluster response and covariate variables, providing update rules, rank se…

stat.ME2026

NMF-FFB: Non-negative matrix factorization with feedforward-feedback structure

Kenichi Satoh

Non-negative matrix factorization (NMF) approximates a non-negative endogenous data matrix as , with non-negative latent components and coefficients . Standa…

stat.ME2026

Wild Bootstrap Inference for Non-Negative Matrix Factorization with Random Effects

Kenichi Satoh

Non-negative matrix factorization (NMF) is widely used for parts-based representations, yet formal inference for covariate effects is rarely available when the basis is learned und…

cs.LG2025

Applying non-negative matrix factorization with covariates to label matrix for classification

Kenichi Satoh

Non-negative matrix factorization (NMF) is widely used for dimensionality reduction and interpretable analysis, but standard formulations are unsupervised and cannot directly explo…