Clustering of functional data in a low-dimensional subspace. - Michio Yamamoto (Adv. Data Anal. Classif., 2012)

Estimation of an oblique structure via penalized likelihood factor analysis. - Kei Hirose; Michio Yamamoto (Comput. Stat. Data Anal., 2014)

Functional factorial K-means analysis. - Michio Yamamoto; Yoshikazu Terada (Comput. Stat. Data Anal., 2014)

Clustering of multivariate binary data with dimension reduction via L1-regularized likelihood maximization. - Michio Yamamoto; Kenichi Hayashi (Pattern Recognit., 2015)

Sparse estimation via nonconcave penalized likelihood in factor analysis model. - Kei Hirose; Michio Yamamoto (Stat. Comput., 2015)

Dimension-Reduced Clustering of Functional Data via Subspace Separation. - Michio Yamamoto; Heungsun Hwang (J. Classif., 2017)

Kernel Normalized Cut: a Theoretical Revisit. - Yoshikazu Terada; Michio Yamamoto (ICML, 2019)

Causal Discovery with Multi-Domain LiNGAM for Latent Factors. - Yan Zeng 002; Shohei Shimizu; Ruichu Cai; Feng Xie 002; Michio Yamamoto; Zhifeng Hao (IJCAI, 2021)

Empathetic Robot Judge, we Trust You. - Eiichiro Watamura; Tomohiro Ioku; Tomoya Mukai; Michio Yamamoto (Int. J. Hum. Comput. Interact., 2024)