A subclass-based mixture model for pattern recognition. - Mineichi Kudo; Hiroshi Tenmoto; Satoru Sumiyoshi; Masaru Shimbo (ICPR, 1998)

Appropriate initial component densities of mixture modeling for pattern recognition. - Mineichi Kudo; F. Taniguchi; Hiroshi Tenmoto; Masaru Shimbo (KES (2), 1998)

MDL-Based Selection of the Number of Components in Mixture Models for Pattern Classification. - Hiroshi Tenmoto; Mineichi Kudo; Masaru Shimbo (SSPR/SPR, 1998)

Piecewise linear classifiers preserving high local recognition rates. - Hiroshi Tenmoto; Mineichi Kudo; Masaru Shimbo (Kybernetika, 1998)

Piecewise linear classifiers with an appropriate number of hyperplanes. - Hiroshi Tenmoto; Mineichi Kudo; Masaru Shimbo (Pattern Recognit., 1998)

Determination of the number of components based on class separability in mixture-based classifiers. - Hiroshi Tenmoto; Mineichi Kudo; Masaru Shimbo (KES, 1999)

Selection of the Number of Components Using a Genetic Algorithm for Mixture Model Classifiers. - Hiroshi Tenmoto; Mineichi Kudo; Masaru Shimbo (SSPR/SPR, 2000)

Classifier-Independent Visualization of Supervised Data Structures Using a Graph. - Hiroshi Tenmoto; Yasukuni Mori; Mineichi Kudo (SSPR/SPR, 2004)

Finding and Auto-labeling of Task Groups on E-Mails and Documents. - Hiroshi Tenmoto; Mineichi Kudo (KES (4), 2005)

Density- and Complexity-Regularization in Gaussian Mixture Bayesian Classifier. - Hiroshi Tenmoto; Mineichi Kudo (WSTST, 2005)

A Combination of Sample Subsets and Feature Subsets in One-Against-Other Classifiers. - Mineichi Kudo; Satoshi Shirai; Hiroshi Tenmoto (MCS, 2007)

Soft Feature Selection by Using a Histogram-Based Classifier. - Hiroshi Tenmoto; Mineichi Kudo (SSPR/SPR, 2008)

Signal Learning with Messages by Reinforcement Learning in Multi-agent Pursuit Problem. - Kozue Noro; Hiroshi Tenmoto; Akimoto Kamiya (KES, 2014)

Simultaneous visualization of samples, features and multi-labels. - Mineichi Kudo; Keigo Kimura; Michal Haindl; Hiroshi Tenmoto (ICPR, 2016)