Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy

2 May 2024

Papers citing "Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy"

7 / 7 papers shown

Title
PREAMBLE: Private and Efficient Aggregation of Block Sparse Vectors and Applications Hilal Asi Vitaly Feldman Hannah Keller G. Rothblum Kunal Talwar FedML 59 1 0 14 Mar 2025
Leveraging Randomness in Model and Data Partitioning for Privacy Amplification Andy Dong Wei-Ning Chen Ayfer Özgür FedML 59 1 0 04 Mar 2025
Sparse Random Networks for Communication-Efficient Federated Learning Berivan Isik Francesco Pase Deniz Gunduz Tsachy Weissman M. Zorzi FedML 70 52 0 30 Sep 2022
DRIVE: One-bit Distributed Mean Estimation S. Vargaftik Ran Ben-Basat Amit Portnoy Gal Mendelson Y. Ben-Itzhak Michael Mitzenmacher OOD FedML 82 51 0 18 May 2021
Practical and Private (Deep) Learning without Sampling or Shuffling Peter Kairouz Brendan McMahan Shuang Song Om Thakkar Abhradeep Thakurta Zheng Xu FedML 182 154 0 26 Feb 2021
An Information-Theoretic Justification for Model Pruning Berivan Isik Tsachy Weissman Albert No 95 35 0 16 Feb 2021
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 150 420 0 29 Nov 2018