AI RESEARCH
PE-means: Improved Differentially Private $k$-means Clustering through Private Evolution
arXiv CS.LG
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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