Shuichi Kawano

According to our database, Shuichi Kawano authored at least 22 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Multi-task learning via robust regularized clustering with non-convex group penalties.

Akira Okazaki, Shuichi Kawano

CoRR, 2024

2023

Sparse Bayesian Learning With Weakly Informative Hyperprior and Extended Predictive Information Criterion.

Kazuaki Murayama, Shuichi Kawano

IEEE Trans. Neural Networks Learn. Syst., September, 2023

Correction: Sparse reduced-rank regression for simultaneous rank and variable selection via manifold optimization.

Kohei Yoshikawa, Shuichi Kawano

Comput. Stat., March, 2023

Sparse reduced-rank regression for simultaneous rank and variable selection via manifold optimization.

Kohei Yoshikawa, Shuichi Kawano

Comput. Stat., March, 2023

Smoothly varying regularization.

Daeju Kim, Shuichi Kawano, Yoshiyuki Ninomiya

Comput. Stat. Data Anal., 2023

2022

Multi-Task Learning for Compositional Data via Sparse Network Lasso.

Akira Okazaki, Shuichi Kawano

Entropy, December, 2022

2021

Multilinear Common Component Analysis via Kronecker Product Representation.

Kohei Yoshikawa, Shuichi Kawano

Neural Comput., 2021

Bayesian sparse convex clustering via global-local shrinkage priors.

Kaito Shimamura, Shuichi Kawano

Comput. Stat., 2021

A Bayesian approach to multi-task learning with network lasso.

Kaito Shimamura, Shuichi Kawano

CoRR, 2021

Sparse principal component regression via singular value decomposition approach.

Shuichi Kawano

Adv. Data Anal. Classif., 2021

Discriminant Analysis via Smoothly Varying Regularization.

Hisao Yoshida, Shuichi Kawano, Yoshiyuki Ninomiya

Proceedings of the Intelligent Decision Technologies, 2021

Variable Fusion for Bayesian Linear Regression via Spike-and-slab Priors.

Shengyi Wu, Kaito Shimamura, Kohei Yoshikawa, Kazuaki Murayama, Shuichi Kawano

Proceedings of the Intelligent Decision Technologies, 2021

2020

Relevance Vector Machine with Weakly Informative Hyperprior and Extended Predictive Information Criterion.

Kazuaki Murayama, Shuichi Kawano

CoRR, 2020

2018

Sparse principal component regression for generalized linear models.

Shuichi Kawano, Hironori Fujisawa, Toyoyuki Takada, Toshihiko Shiroishi

Comput. Stat. Data Anal., 2018

2015

Sparse principal component regression with adaptive loading.

Shuichi Kawano, Hironori Fujisawa, Toyoyuki Takada, Toshihiko Shiroishi

Comput. Stat. Data Anal., 2015

Constraint-Based Learning Bayesian Networks Using Bayes Factor.

Kazuki Natori, Masaki Uto, Yu Nishiyama, Shuichi Kawano, Maomi Ueno

Proceedings of the Advanced Methodologies for Bayesian Networks, 2015

2014

Adaptive basis expansion via (ℓ₁) trend filtering.

Daeju Kim, Shuichi Kawano, Yoshiyuki Ninomiya

Comput. Stat., 2014

2013

Semi-supervised logistic discrimination via labeled data and unlabeled data from different sampling distributions.

Shuichi Kawano

Stat. Anal. Data Min., 2013

2012

Identifying Gene Pathways Associated with Cancer Characteristics via Sparse Statistical Methods.

Shuichi Kawano, Teppei Shimamura, Atsushi Niida, Seiya Imoto, Rui Yamaguchi, Masao Nagasaki, Ryo Yoshida, Cristin G. Print, Satoru Miyano

IEEE ACM Trans. Comput. Biol. Bioinform., 2012

Semi-Supervised Logistic Discrimination Via Graph-Based Regularization.

Shuichi Kawano, Toshihiro Misumi, Sadanori Konishi

Neural Process. Lett., 2012

2010

Discovering functional gene pathways associated with cancer heterogeneity via sparse supervised learning.

Shuichi Kawano, Teppei Shimamura, Atsushi Niida, Seiya Imoto, Rui Yamaguchi, Masao Nagasaki, Ryo Yoshida, Cristin G. Print, Satoru Miyano

Proceedings of the 2010 IEEE International Conference on Bioinformatics and Biomedicine, 2010

2009

Nonlinear Logistic Discrimination Via Regularized Gaussian Basis Expansions.

Shuichi Kawano, Sadanori Konishi

Commun. Stat. Simul. Comput., 2009