Utility-efficient Differentially Private K-means Clustering based on Cluster Merging

3 October 2020

Papers citing "Utility-efficient Differentially Private K-means Clustering based on Cluster Merging"

5 / 5 papers shown

Title
FastLloyd: Federated, Accurate, Secure, and Tunable $k$ -Means Clustering with Differential Privacy Abdulrahman Diaa Thomas Humphries Florian Kerschbaum FedML 71 0 0 03 May 2024
Locally Private k-Means Clustering Uri Stemmer FedML 89 58 0 04 Jul 2019
Deep $k$ -Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions Junru Wu Yue Wang Zhenyu Wu Zhangyang Wang Ashok Veeraraghavan Yingyan Lin 59 115 0 24 Jun 2018
Differentially Private $k$ -Means Clustering D. Su Jianneng Cao Ninghui Li E. Bertino Hongxia Jin 40 153 0 22 Apr 2015
Protecting Locations with Differential Privacy under Temporal Correlations Yonghui Xiao Li Xiong 79 379 0 22 Oct 2014