Locally Private k-Means in One Round

20 April 2021

Papers citing "Locally Private k-Means in One Round"

8 / 8 papers shown

Title
FastLloyd: Federated, Accurate, Secure, and Tunable $k$ -Means Clustering with Differential Privacy Abdulrahman Diaa Thomas Humphries Florian Kerschbaum FedML 26 0 0 03 May 2024
Differential Privacy for Clustering Under Continual Observation Max Dupré la Tour Monika Henzinger David Saulpic 15 1 0 07 Jul 2023
Differentially Private Vertical Federated Clustering Zitao Li Tianhao Wang Ninghui Li FedML 21 18 0 02 Aug 2022
Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message Badih Ghazi Ravi Kumar Pasin Manurangsi Rasmus Pagh Amer Sinha FedML 55 36 0 27 Sep 2021
Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead Badih Ghazi Ravi Kumar Pasin Manurangsi Rasmus Pagh FedML 24 48 0 08 Jun 2021
Private Aggregation from Fewer Anonymous Messages Badih Ghazi Pasin Manurangsi Rasmus Pagh A. Velingker FedML 37 55 0 24 Sep 2019
Locally Private k-Means Clustering Uri Stemmer FedML 21 56 0 04 Jul 2019
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 136 420 0 29 Nov 2018