A note on differentially private clustering with large additive error

Autor:	Nguyen, Huy L.
Rok vydání:	2020
Předmět:	Computer Science - Data Structures and Algorithms Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	In this note, we describe a simple approach to obtain a differentially private algorithm for k-clustering with nearly the same multiplicative factor as any non-private counterpart at the cost of a large polynomial additive error. The approach is the combination of a simple geometric observation independent of privacy consideration and any existing private algorithm with a constant approximation.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2009.13317 Zobrazit plný text záznamu View this record from Arxiv