AI RESEARCH

PE-means: Improved Differentially Private $k$-means Clustering through Private Evolution

arXiv CS.LG

ArXi:2606.00342v1 Announce Type: new We study the problem of differentially private (DP) $k$-means clustering in Euclidean space. Previous solutions rely on summing the private data directly, which induces a sensitivity proportional to the domain. We