1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2026
Nonlinear Data Integration via Kernel Methods for Data Collaboration Analysis
Yamato Suetake, Yuta Kawakami, Shunnosuke Ikeda +1
Collaborative analysis of decentralized confidential datasets is important, but direct sharing of original datasets is often restricted by privacy and institutional constraints. Da…
cs.LG2024★ 1 cited
New Solutions Based on the Generalized Eigenvalue Problem for the Data Collaboration Analysis
Yuta Kawakami, Yuichi Takano, Akira Imakura
In recent years, the accumulation of data across various institutions has garnered attention for the technology of confidential data analysis, which improves analytical accuracy by…