Dimension Selection for Feature Selection and Dimension Reduction with Principal and Independent Component Analysis. - Inge Koch; Kanta Naito (Neural Comput., 2007)

Bandwidth selection for a data sharpening estimator in nonparametric regression. - Kanta Naito; Masahiro Yoshizaki (J. Multivar. Anal., 2009)

Prediction of multivariate responses with a selected number of principal components. - Inge Koch; Kanta Naito (Comput. Stat. Data Anal., 2010)

A computationally efficient model selection in the generalized linear mixed model. - Takuma Yoshida; Masaru Kanba; Kanta Naito (Comput. Stat., 2010)

Pattern recognition based on canonical correlations in a high dimension low sample size context. - Mitsuru Tamatani; Inge Koch; Kanta Naito (J. Multivar. Anal., 2012)

Density estimation with minimization of U-divergence. - Kanta Naito; Shinto Eguchi (Mach. Learn., 2013)

Locally robust methods and near-parametric asymptotics. - Spiridon I. Penev; Kanta Naito (J. Multivar. Anal., 2018)

Regression with stagewise minimization on risk function. - Takuma Yoshida; Kanta Naito (Comput. Stat. Data Anal., 2019)

Asymptotics and practical aspects of testing normality with kernel methods. - Natsumi Makigusa; Kanta Naito (J. Multivar. Anal., 2020)

Support vector regression with penalized likelihood. - Takumi Uemoto; Kanta Naito (Comput. Stat. Data Anal., 2022)

Simultaneous confidence region of an embedded one-dimensional curve in multi-dimensional space. - Hiroya Yamazoe; Kanta Naito (Comput. Stat. Data Anal., 2024)

Kernel density estimation by stagewise algorithm with a simple dictionary. - Kiheiji Nishida; Kanta Naito (Comput. Stat., 2024)

Semiparametric density estimation with localized Bregman divergence. - Daisuke Matsuno; Kanta Naito (J. Multivar. Anal., 2025)