Making Old Things New: A Unified Algorithm for Differentially Private Clustering

arXiv:2406.11649v1 Announce Type: cross
Abstract: As a staple of data analysis and unsupervised learning, the problem of private clustering has been widely studied under various privacy models. Centralized differential privacy is the first of them, and the problem has also been studied for the local and the shuffle variation. In each case, the goal is to design an algorithm that computes privately a clustering, with the smallest possible error. The study of each variation gave rise to new algorithms: the …

abstract algorithm analysis arxiv clustering cs.cr cs.ds cs.lg data data analysis differential differential privacy making privacy problem them things type unsupervised unsupervised learning variation