Shuichi Kawano

31 papers Journal 27Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Simultaneous modeling of disease screening and severity prediction: A multi-task and sparse regularization approach. Expert Syst. Appl. Kazuharu Harada, Shuichi Kawano, Masataka Taguri
2025	J	`jnl`	DAG Learning from Zero-Inflated Count Data Using Continuous Optimization. CoRR Noriaki Sato, Marco Scutari, Shuichi Kawano, Rui Yamaguchi, Seiya Imoto
2025	J	`jnl`	Multi-task learning via robust regularized clustering with non-convex group penalties. Stat. Comput. Akira Okazaki, Shuichi Kawano
2025	J	`jnl`	Practical Causal Evaluation Metrics for Biological Networks. CoRR Noriaki Sato, Marco Scutari, Shuichi Kawano, Rui Yamaguchi, Seiya Imoto
2024	J	`jnl`	Multi-task learning regression via convex clustering. Comput. Stat. Data Anal. Akira Okazaki, Shuichi Kawano
2024	J	`jnl`	Multi-task learning via robust regularized clustering with non-convex group penalties. CoRR Akira Okazaki, Shuichi Kawano
2023	J	`jnl`	Correction: Sparse reduced-rank regression for simultaneous rank and variable selection via manifold optimization. Comput. Stat. Kohei Yoshikawa, Shuichi Kawano
2023	J	`jnl`	Smoothly varying regularization. Comput. Stat. Data Anal. Daeju Kim, Shuichi Kawano, Yoshiyuki Ninomiya
2023	J	`jnl`	Sparse Bayesian Learning With Weakly Informative Hyperprior and Extended Predictive Information Criterion. IEEE Trans. Neural Networks Learn. Syst. Kazuaki Murayama, Shuichi Kawano
2023	J	`jnl`	Sparse reduced-rank regression for simultaneous rank and variable selection via manifold optimization. Comput. Stat. Kohei Yoshikawa, Shuichi Kawano
2022	J	`jnl`	Multi-Task Learning for Compositional Data via Sparse Network Lasso. Entropy Akira Okazaki, Shuichi Kawano
2021	J	`jnl`	A Bayesian approach to multi-task learning with network lasso. CoRR Kaito Shimamura, Shuichi Kawano
2021	J	`jnl`	Bayesian sparse convex clustering via global-local shrinkage priors. Comput. Stat. Kaito Shimamura, Shuichi Kawano
2021	—	`conf`	Discriminant Analysis via Smoothly Varying Regularization. KES-IDT Hisao Yoshida, Shuichi Kawano, Yoshiyuki Ninomiya
2021	J	`jnl`	Multilinear Common Component Analysis via Kronecker Product Representation. Neural Comput. Kohei Yoshikawa, Shuichi Kawano
2021	J	`jnl`	Sparse principal component regression via singular value decomposition approach. Adv. Data Anal. Classif. Shuichi Kawano
2021	—	`conf`	Variable Fusion for Bayesian Linear Regression via Spike-and-slab Priors. KES-IDT Shengyi Wu, Kaito Shimamura, Kohei Yoshikawa, Kazuaki Murayama, Shuichi Kawano
2020	J	`jnl`	Multilinear Common Component Analysis via Kronecker Product Representation. CoRR Kohei Yoshikawa, Shuichi Kawano
2020	J	`jnl`	Relevance Vector Machine with Weakly Informative Hyperprior and Extended Predictive Information Criterion. CoRR Kazuaki Murayama, Shuichi Kawano
2020	J	`jnl`	Sparse principal component regression via singular value decomposition approach. CoRR Shuichi Kawano
2019	J	`jnl`	Bayesian sparse convex clustering via global-local shrinkage priors. CoRR Kaito Shimamura, Shuichi Kawano
2019	J	`jnl`	Sparse Reduced-Rank Regression for Simultaneous Rank and Variable Selection via Manifold Optimization. CoRR Kohei Yoshikawa, Shuichi Kawano
2018	J	`jnl`	Sparse principal component regression for generalized linear models. Comput. Stat. Data Anal. Shuichi Kawano, Hironori Fujisawa, Toyoyuki Takada, Toshihiko Shiroishi
2015	—	`conf`	Constraint-Based Learning Bayesian Networks Using Bayes Factor. AMBN@JSAI-isAI Kazuki Natori, Masaki Uto, Yu Nishiyama, Shuichi Kawano, Maomi Ueno
2015	J	`jnl`	Sparse principal component regression with adaptive loading. Comput. Stat. Data Anal. Shuichi Kawano, Hironori Fujisawa, Toyoyuki Takada, Toshihiko Shiroishi
2014	J	`jnl`	Adaptive basis expansion via (ℓ Comput. Stat. Daeju Kim, Shuichi Kawano, Yoshiyuki Ninomiya
2013	J	`jnl`	Semi-supervised logistic discrimination via labeled data and unlabeled data from different sampling distributions. Stat. Anal. Data Min. Shuichi Kawano
2012	J	`jnl`	Identifying Gene Pathways Associated with Cancer Characteristics via Sparse Statistical Methods. IEEE ACM Trans. Comput. Biol. Bioinform. Shuichi Kawano, Teppei Shimamura, Atsushi Niida, Seiya Imoto, Rui Yamaguchi, Masao Nagasaki, Ryo Yoshida, Cristin G. Print, Satoru Miyano
2012	J	`jnl`	Semi-Supervised Logistic Discrimination Via Graph-Based Regularization. Neural Process. Lett. Shuichi Kawano, Toshihiro Misumi, Sadanori Konishi
2010	—	`conf`	Discovering functional gene pathways associated with cancer heterogeneity via sparse supervised learning. BIBM Shuichi Kawano, Teppei Shimamura, Atsushi Niida, Seiya Imoto, Rui Yamaguchi, Masao Nagasaki, Ryo Yoshida, Cristin G. Print, Satoru Miyano
2009	J	`jnl`	Nonlinear Logistic Discrimination Via Regularized Gaussian Basis Expansions. Commun. Stat. Simul. Comput. Shuichi Kawano, Sadanori Konishi