AI RESEARCH
Nonlinear Data Integration via Kernel Methods for Data Collaboration Analysis
arXiv CS.LG
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ArXi:2605.27219v1 Announce Type: new Collaborative analysis of decentralized confidential datasets is important, but direct sharing of original datasets is often restricted by privacy and institutional constraints. Data collaboration (DC) analysis transforms each dataset into privacy-preserving intermediate representations via party-specific obfuscation functions and integrates them into common collaboration representations using an anchor dataset.