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ORCIDShuichi Kawano
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2020 – today
- 2024
[j16]Akira Okazaki
, Shuichi Kawano:
Multi-task learning regression via convex clustering. Comput. Stat. Data Anal. 195: 107956 (2024)- [i7]Akira Okazaki, Shuichi Kawano:
Multi-task learning via robust regularized clustering with non-convex group penalties. CoRR abs/2404.03250 (2024) - 2023
- [j15]Daeju Kim, Shuichi Kawano, Yoshiyuki Ninomiya:
Smoothly varying regularization. Comput. Stat. Data Anal. 179: 107644 (2023) - [j14]Kohei Yoshikawa, Shuichi Kawano:
Sparse reduced-rank regression for simultaneous rank and variable selection via manifold optimization. Comput. Stat. 38(1): 53-75 (2023) - [j13]Kohei Yoshikawa, Shuichi Kawano:
Correction: Sparse reduced-rank regression for simultaneous rank and variable selection via manifold optimization. Comput. Stat. 38(1): 77-78 (2023) - [j12]Kazuaki Murayama, Shuichi Kawano:
Sparse Bayesian Learning With Weakly Informative Hyperprior and Extended Predictive Information Criterion. IEEE Trans. Neural Networks Learn. Syst. 34(9): 5856-5868 (2023) - 2022
- [j11]Akira Okazaki, Shuichi Kawano:
Multi-Task Learning for Compositional Data via Sparse Network Lasso. Entropy 24(12): 1839 (2022) - 2021
- [j10]Shuichi Kawano:
Sparse principal component regression via singular value decomposition approach. Adv. Data Anal. Classif. 15(3): 795-823 (2021) - [j9]Kaito Shimamura, Shuichi Kawano:
Bayesian sparse convex clustering via global-local shrinkage priors. Comput. Stat. 36(4): 2671-2699 (2021) - [j8]Kohei Yoshikawa, Shuichi Kawano:
Multilinear Common Component Analysis via Kronecker Product Representation. Neural Comput. 33(10): 2853-2880 (2021) - [c4]Hisao Yoshida, Shuichi Kawano, Yoshiyuki Ninomiya:
Discriminant Analysis via Smoothly Varying Regularization. KES-IDT 2021: 441-455 - [c3]Shengyi Wu, Kaito Shimamura, Kohei Yoshikawa, Kazuaki Murayama, Shuichi Kawano:
Variable Fusion for Bayesian Linear Regression via Spike-and-slab Priors. KES-IDT 2021: 491-501 - [i6]Kaito Shimamura, Shuichi Kawano:
A Bayesian approach to multi-task learning with network lasso. CoRR abs/2110.09040 (2021) - 2020
- [i5]Shuichi Kawano:
Sparse principal component regression via singular value decomposition approach. CoRR abs/2002.09188 (2020) - [i4]Kazuaki Murayama, Shuichi Kawano:
Relevance Vector Machine with Weakly Informative Hyperprior and Extended Predictive Information Criterion. CoRR abs/2005.03419 (2020) - [i3]Kohei Yoshikawa, Shuichi Kawano:
Multilinear Common Component Analysis via Kronecker Product Representation. CoRR abs/2009.02695 (2020)
2010 – 2019
- 2019
- [i2]Kohei Yoshikawa, Shuichi Kawano:
Sparse Reduced-Rank Regression for Simultaneous Rank and Variable Selection via Manifold Optimization. CoRR abs/1910.05083 (2019) - [i1]Kaito Shimamura, Shuichi Kawano:
Bayesian sparse convex clustering via global-local shrinkage priors. CoRR abs/1911.08703 (2019) - 2018
- [j7]Shuichi Kawano, Hironori Fujisawa, Toyoyuki Takada, Toshihiko Shiroishi:
Sparse principal component regression for generalized linear models. Comput. Stat. Data Anal. 124: 180-196 (2018) - 2015
- [j6]Shuichi Kawano, Hironori Fujisawa, Toyoyuki Takada, Toshihiko Shiroishi:
Sparse principal component regression with adaptive loading. Comput. Stat. Data Anal. 89: 192-203 (2015) - [c2]Kazuki Natori, Masaki Uto, Yu Nishiyama, Shuichi Kawano, Maomi Ueno:
Constraint-Based Learning Bayesian Networks Using Bayes Factor. AMBN@JSAI-isAI 2015: 15-31 - 2014
- [j5]Daeju Kim, Shuichi Kawano, Yoshiyuki Ninomiya:
Adaptive basis expansion via (ℓ1) trend filtering. Comput. Stat. 29(5): 1005-1023 (2014) - 2013
- [j4]Shuichi Kawano:
Semi-supervised logistic discrimination via labeled data and unlabeled data from different sampling distributions. Stat. Anal. Data Min. 6(6): 472-481 (2013) - 2012
- [j3]Shuichi Kawano, Toshihiro Misumi, Sadanori Konishi:
Semi-Supervised Logistic Discrimination Via Graph-Based Regularization. Neural Process. Lett. 36(3): 203-216 (2012) - [j2]Shuichi Kawano, Teppei Shimamura, Atsushi Niida, Seiya Imoto, Rui Yamaguchi, Masao Nagasaki, Ryo Yoshida, Cristin G. Print, Satoru Miyano:
Identifying Gene Pathways Associated with Cancer Characteristics via Sparse Statistical Methods. IEEE ACM Trans. Comput. Biol. Bioinform. 9(4): 966-972 (2012) - 2010
- [c1]Shuichi Kawano, Teppei Shimamura, Atsushi Niida, Seiya Imoto, Rui Yamaguchi, Masao Nagasaki, Ryo Yoshida, Cristin G. Print, Satoru Miyano:
Discovering functional gene pathways associated with cancer heterogeneity via sparse supervised learning. BIBM 2010: 253-258
2000 – 2009
- 2009
- [j1]Shuichi Kawano, Sadanori Konishi:
Nonlinear Logistic Discrimination Via Regularized Gaussian Basis Expansions. Commun. Stat. Simul. Comput. 38(7): 1414-1425 (2009)
Coauthor Index
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