Presentations

[34] *Okazaki, A. and Kawano, S. “Multi-task learning regression via robust convex clustering” 2024 Joint Statistical Meetings (2024JSM)@Portland, Oregon Convention Center. 2024年8月.

[33] *Okazaki, A. and Kawano, S. “Multi-task learning regression based on convex clustering” The 16th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics2023)@Berlin, HTW Berlin. 2023年12月.

[32] *Kawano, S., Fukushima, T., Nakagawa, J. and Oshiki, M. “Integrative multivariate regression analysis via penalization” The 16th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics2023)@Berlin, HTW Berlin. 2023年12月.

[31] *Fukushima, T., Kawano, S., Oshiki, M. and Nakagawa, J. “Development of statistical method for identification of microorganisms responsible for wastewater treatment” The 9th IWA-ASPIRE Conference and Exhibition 2023@Kaohsiung, Kaohsiung Marriott Hotel. 2023年10月.

[30] *Harada, K., Kawano, S. and Taguri, M. “Modeling and estimation for hierarchical ordinal outcome” The 44th Annual Conference of the International Society for Clinical Biostatistics (ISCB44)@Milan, University of Milano Bicocca. 2023年8月. (ポスター発表)

[29] Yoshikawa, K. and *Kawano, S. “Multilinear common component analysis for tensor data based on Kronecker product approach” The 5th International Conference on Econometrics and Statistics (EcoSta 2022)@Kyoto, Ryukoku University. 2022年6月. (Invited)

[28] *Okazaki, A. and Kawano, S. “Multi-task learning for compositional data based on sparse network lasso regularization” The 5th International Conference on Econometrics and Statistics (EcoSta 2022)@Kyoto, Ryukoku University. 2022年6月.

[27] *Kakikawa, Y., Shimamura, K. and Kawano, S. “Bayesian fused lasso and Bayesian HORSES via horseshoe prior” The 5th International Conference on Econometrics and Statistics (EcoSta 2022)@Kyoto, Ryukoku University. 2022年6月.

[26] *Fukushima, T., Kawano, S., Oshiki, M. and Nakagawa, J. “Development of statistical method for identification of microorganisms responsible for wastewater treatment” The 9th Microbial Ecology & Water Engineering (MEWE) Specialist Conference of the International Water Association (IWA), Online. 2021年10月.（ポスター発表)

[25] Yoshida, H., Kawano, S. and *Ninomiya, Y. “Discriminant analysis via smoothly varying regularization“ The 13th KES International Conference on Intelligent Decision Technologies (KES-IDT-21), Online. 2021年6月. (Invited)

[24] Wu, S., Shimamura, K., Yoshikawa, K., Murayama, K. and *Kawano, S. “Variable fusion for Bayesian linear regression via spike-and-slab priors“ The 13th KES International Conference on Intelligent Decision Technologies (KES-IDT-21), Online. 2021年6月. (Invited)

[23] *Shimamura, K. and Kawano, S. “Bayesian sparse convex clustering via NEG distribution” The 12th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics2019)@London, University of London. 2019年12月.

[22] *Kawano, S. Sparse principal component regression via singular value decomposition” The 11th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics2018)@Pisa, University of Pisa. 2018年12月. (Invited)

[21] *Yamasaki, Y., Fujita, M., Kawano, S. and Baba, T. “Effect of salinity on interspecific competition between Alexandrium catenella and Heterosigma akashiwo” The 18th International Conference on Harmful Algae (ICHA2018)@Nantes, La Cité Nantes Events Center. 2018年10月.（ポスター発表)

[20] *Kawano, S., Fujisawa, H., Takada, T. and Shiroishi, T. “A one-stage estimation of principal component regression for generalized linear models” The 2nd International Conference on Econometrics and Statistics (EcoSta 2018)@Hong Kong, City University of Hong Kong. 2018年6月. (Invited)

[19] *Kawano, S., Fujisawa, H., Takada, T. and Shiroishi, T. “Principal component regression for generalized linear models via L1-type regularization” The 10th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics2017)@London, University of London. 2017年12月.

[18] *Kawano, S., Fujisawa, H., Takada, T. and Shiroishi, T. “A one-stage principal component regression method with sparse regularization” 2016 CSA & NCCU Joint Statistical Meetings (In Celebration of the 50th Anniversary of Department of Statistics)@Taipei, National Chengchi University. 2016年12月. (Invited)

[17] *Kawano, S., Fujisawa, H., Takada, T. and Shiroishi, T. “A one-stage approach for principal component regression via L1-type regularization” The 4th IMS-APRM@Hong Kong, The Chinese University of Hong Kong. 2016年6月.

[16] *Kawano, S., Fujisawa, H., Takada, T. and Shiroishi, T. “One-stage estimation of principal component regression with sparse regularization” The 8th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics2015)@London, University of London. 2015年12月.

[15] *Natori, K., Uto, M., Nishiyama, Y., Kawano, S. and Ueno, M. “Constraint-based learning Bayesian networks using Bayes factor” The 2nd Workshop on Advanced Methodologies for Bayesian Networks (AMBN2015)@Yokohama, Keio University. 2015年11月.

[14] *Kawano, S. and Fujisawa, H. “Sparse principal component regression for simultaneous dimension reduction and variable selection” The 3rd IMS-APRM@Taipei, Howard International House. 2014年6月.（ポスター発表)

[13] *Ninomiya, Y. and Kawano, S. “AIC-type information criterion for LASSO” The 3rd IMS-APRM@Taipei, Howard International House. 2014年6月.（ポスター発表)

[12] *Kawano, S. “Tuning parameter selection in bridge regression modeling”  Joint Statistical Meetings 2013@Montréal, Palais des congrès de Montréal. 2013年8月.

[11] *Kim, T., Kawano, S. and Ninomiya, Y. “Curve and surface estimation via adaptive basis expansions” Forum “Math-for-Industry” 2012@Fukuoka, Fukuoka International Congress Center. 2012年10月.（ポスター発表)

[10] *Kawano, S. “Weighted logistic regression modeling for semi-supervised classification” Joint Statistical Meetings 2012@San Diego, San Diego Convention Center. 2012年7月.

[9] *Kim, T., Kawano, S. and Ninomiya, Y. “Nonlinear regression modeling via adaptive penalty” The 8th World Congress in Probability and Statistics@Istanbul, Grand Cevahir Hotel & Convention Center. 2012年7月.（ポスター発表)

[8] *Kim, T., Kawano, S. and Ninomiya, Y. “Adaptive basis expansions for nonlinear regression models” The 2nd IMS-APRM@Tsukuba, Tsukuba International Congress Center. 2012年7月.（ポスター発表)

[7] *Kim, T., Kawano, S. and Ninomiya, Y. “Adaptive basis expansion method for nonlinear regression model” Forum “Math-for-Industry” 2011@Hawaii, University of Hawaii. 2011年10月.（ポスター発表)

[6] *Kawano, S., Shimamura, T., Niida, A., Imoto, S., Yamaguchi, R., Nagasaki, M., Yoshida, R., Print, C. and Miyano, S. “Discovering functional gene pathways associated with cancer heterogeneity via sparse supervised learning” IEEE International Conference on Bioinformatics and Biomedicine@Hong Kong, The Chinese University of Hong Kong. 2010年12月.

[5] *Kawano, S. and Konishi, S. “Semi-supervised learning via regularized logistic discrimination” Joint Statistical Meetings 2009@Washington, DC,  Walter E. Washington Convention Center. 2009年8月.

[4] *Hirose, K., Kawano, S., Konishi, S. and Ichikawa, M. “A choice of the number of factors and hyper-parameter selection in Bayesian factor analysis model” Joint Statistical Meetings 2009@Washington, DC,  Walter E. Washington Convention Center. 2009年8月.

[3] *Kawano, S. and Konishi, S. “Semi-supervised logistic discrimination via regularized basis expansions” The 7th World Congress in Probability and Statistics@Singapore, National University of Singapore. 2008年7月.

[2] *Hirose, K., Kawano, S., Konishi, S. and Ichikawa, M. “Selection of the number of factors in Bayesian factor analysis” The 7th World Congress in Probability and Statistics@Singapore, National University of Singapore. 2008年7月.

[1] *Matsui, H., Kawano, S., Kayano, M. and Konishi, S. “Regularized functional regression modeling for functional response and predictors” The 56th Session of the International Statistical Institute@Lisboa, Lisboa Congress Centre. 2007年8月.