Author

Kensuke Tanioka

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Open access Sep 2026

Cooperative Learning with Penalized Linear Mixed-Effects Models for High-Dimensional Clustered Multiview Data

In biomedical research, multiple types of high-dimensional data, such as genomic, transcriptomic, proteomic, and metabolomic data, are increasingly collected from the same subjects. Integrating these multiple data views can improve prediction by exploiting shared or complementary information across the views. Cooperati...

Shunsuke Yoshimura, Mariko Takagishi, Kensuke Tanioka · bioRxiv · 0 citations

#machine learning Preprint Sep 2026

Geographically Regularized AUC-Maximizing Personalized Federated Learning

Accurate diagnostic and risk-prediction models are important for supporting clinical decision-making during infectious disease outbreaks. However, privacy and governance requirements may restrict patient-level data sharing across healthcare institutions, and data distributions often vary. Moreover, AUC is widely used t...

Mayu Hiraishi, Kensuke Tanioka, Toshio Shimokawa · 0 citations