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Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging

10 June 2022

Laurent Massoulié

Papers citing "Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging"

30 / 30 papers shown

Title
PDSL: Privacy-Preserved Decentralized Stochastic Learning with Heterogeneous Data Distribution Lina Wang Yunsheng Yuan Chunxiao Wang Feng Li FedML 99 0 0 31 Mar 2025
Fair Decentralized Learning Sayan Biswas Anne-Marie Kermarrec Rishi Sharma Thibaud Trinca M. Vos FedML 125 0 0 03 Oct 2024
Exponential Graph is Provably Efficient for Decentralized Deep Training Bicheng Ying Kun Yuan Yiming Chen Hanbin Hu Pan Pan W. Yin FedML 88 88 0 26 Oct 2021
Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks D. Kovalev Elnur Gasanov Peter Richtárik Alexander Gasnikov 53 44 0 08 Jun 2021
Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling Vitaly Feldman Audra McMillan Kunal Talwar FedML 79 162 0 23 Dec 2020
Privacy Amplification by Decentralization Edwige Cyffers A. Bellet FedML 105 41 0 09 Dec 2020
Asynchrony and Acceleration in Gossip Algorithms Mathieu Even Hadrien Hendrikx Laurent Massoulié 49 7 0 04 Nov 2020
Individual Privacy Accounting via a Renyi Filter Vitaly Feldman Tijana Zrnic 105 90 0 25 Aug 2020
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates Anastasia Koloskova Nicolas Loizou Sadra Boreiri Martin Jaggi Sebastian U. Stich FedML 85 515 0 23 Mar 2020
Pure Differentially Private Summation from Anonymous Messages Badih Ghazi Noah Golowich Ravi Kumar Pasin Manurangsi Rasmus Pagh A. Velingker FedML 101 46 0 05 Feb 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 275 6,294 0 10 Dec 2019
Differentially Private Summation with Multi-Message Shuffling Borja Balle James Bell Adria Gascon Kobbi Nissim FedML 69 47 0 20 Jun 2019
An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums Hadrien Hendrikx Francis R. Bach Laurent Massoulie 64 31 0 27 May 2019
Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication Anastasia Koloskova Sebastian U. Stich Martin Jaggi FedML 83 511 0 01 Feb 2019
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 199 430 0 29 Nov 2018
Privacy Amplification by Iteration Vitaly Feldman Ilya Mironov Kunal Talwar Abhradeep Thakurta FedML 79 177 0 20 Aug 2018
Distributed Differential Privacy via Shuffling Albert Cheu Adam D. Smith Jonathan R. Ullman David Zeber M. Zhilyaev FedML 95 352 0 04 Aug 2018
Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences Borja Balle Gilles Barthe Marco Gaboardi 87 393 0 04 Jul 2018
Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms Xueru Zhang Mohammad Mahdi Khalili M. Liu FedML 99 91 0 06 Jun 2018
Accelerated Gossip in Networks of Given Dimension using Jacobi Polynomial Iterations Raphael Berthier Francis R. Bach Pierre Gaillard 58 31 0 22 May 2018
Differentially Private Empirical Risk Minimization Revisited: Faster and More General Di Wang Minwei Ye Jinhui Xu 119 272 0 14 Feb 2018
Empirical Risk Minimization in Non-interactive Local Differential Privacy: Efficiency and High Dimensional Case Di Wang Marco Gaboardi Jinhui Xu 91 61 0 12 Feb 2018
Network Topology and Communication-Computation Tradeoffs in Decentralized Optimization A. Nedić Alexander Olshevsky Michael G. Rabbat 74 513 0 26 Sep 2017
Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible Kai Zheng Wenlong Mou Liwei Wang 99 41 0 11 Jun 2017
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent Xiangru Lian Ce Zhang Huan Zhang Cho-Jui Hsieh Wei Zhang Ji Liu 60 1,235 0 25 May 2017
Optimal algorithms for smooth and strongly convex distributed optimization in networks Kevin Scaman Francis R. Bach Sébastien Bubeck Y. Lee Laurent Massoulié 79 331 0 28 Feb 2017
Renyi Differential Privacy Ilya Mironov 91 1,268 0 24 Feb 2017
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 408 17,615 0 17 Feb 2016
Differentially Private Distributed Optimization Zhenqi Huang Sayan Mitra Nitin H. Vaidya FedML 80 268 0 12 Jan 2014
Gossip Algorithms for Distributed Signal Processing A. Dimakis S. Kar José M. F. Moura Michael G. Rabbat Anna Scaglione 148 857 0 27 Mar 2010