Optimizing the Numbers of Queries and Replies in Federated Learning with Differential Privacy

5 July 2021

Papers citing "Optimizing the Numbers of Queries and Replies in Federated Learning with Differential Privacy"

33 / 33 papers shown

Title
Cost-Effective Federated Learning Design Bing Luo Xiang Li Shiqiang Wang Jianwei Huang Leandros Tassiulas FedML 38 180 0 15 Dec 2020
LDP-Fed: Federated Learning with Local Differential Privacy Stacey Truex Ling Liu Ka-Ho Chow Mehmet Emre Gursoy Wenqi Wei FedML 53 392 0 05 Jun 2020
A Framework for Evaluating Gradient Leakage Attacks in Federated Learning Wenqi Wei Ling Liu Margaret Loper Ka-Ho Chow Mehmet Emre Gursoy Stacey Truex Yanzhao Wu FedML 46 147 0 22 Apr 2020
FedSel: Federated SGD under Local Differential Privacy with Top-k Dimension Selection Ruixuan Liu Yang Cao Masatoshi Yoshikawa Hong Chen FedML 34 108 0 24 Mar 2020
Threats to Federated Learning: A Survey Lingjuan Lyu Han Yu Qiang Yang FedML 259 437 0 04 Mar 2020
Wireless Federated Learning with Local Differential Privacy Mohamed Seif Ravi Tandon Ming Li 98 171 0 12 Feb 2020
Convergence Time Optimization for Federated Learning over Wireless Networks Mingzhe Chen H. Vincent Poor Walid Saad Shuguang Cui 51 297 0 22 Jan 2020
iDLG: Improved Deep Leakage from Gradients Bo Zhao Konda Reddy Mopuri Hakan Bilen FedML 57 635 0 08 Jan 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 161 6,226 0 10 Dec 2019
Federated Learning with Bayesian Differential Privacy Aleksei Triastcyn Boi Faltings FedML 45 176 0 22 Nov 2019
Federated Learning with Differential Privacy: Algorithms and Performance Analysis Kang Wei Jun Li Ming Ding Chuan Ma Heng Yang Farokhi Farhad Shi Jin Tony Q.S. Quek H. Vincent Poor FedML 99 1,607 0 01 Nov 2019
Accelerating Federated Learning via Momentum Gradient Descent Wei Liu Li Chen Yunfei Chen Wenyi Zhang FedML AI4CE 60 292 0 08 Oct 2019
Differential Privacy-enabled Federated Learning for Sensitive Health Data Olivia Choudhury A. Gkoulalas-Divanis Theodoros Salonidis I. Sylla Yoonyoung Park Grace Hsu Amar K. Das FedML OOD 47 176 0 07 Oct 2019
Differentially Private Meta-Learning Jeffrey Li M. Khodak S. Caldas Ameet Talwalkar FedML 110 107 0 12 Sep 2019
Federated Learning: Challenges, Methods, and Future Directions Tian Li Anit Kumar Sahu Ameet Talwalkar Virginia Smith FedML 96 4,496 0 21 Aug 2019
On the Convergence of FedAvg on Non-IID Data Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang FedML 127 2,326 0 04 Jul 2019
The Value of Collaboration in Convex Machine Learning with Differential Privacy Nan Wu Farhad Farokhi David B. Smith M. Kâafar FedML 54 98 0 24 Jun 2019
Deep Leakage from Gradients Ligeng Zhu Zhijian Liu Song Han FedML 76 2,199 0 21 Jun 2019
Towards Federated Learning at Scale: System Design Keith Bonawitz Hubert Eichner W. Grieskamp Dzmitry Huba A. Ingerman ... H. B. McMahan Timon Van Overveldt David Petrou Daniel Ramage Jason Roselander FedML 101 2,660 0 04 Feb 2019
LEAF: A Benchmark for Federated Settings S. Caldas Sai Meher Karthik Duddu Peter Wu Tian Li Jakub Konecný H. B. McMahan Virginia Smith Ameet Talwalkar FedML 120 1,417 0 03 Dec 2018
Protection Against Reconstruction and Its Applications in Private Federated Learning Abhishek Bhowmick John C. Duchi Julien Freudiger Gaurav Kapoor Ryan M. Rogers FedML 58 360 0 03 Dec 2018
Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning Peng Kuang Mengkai Song Zhifei Zhang Yang Song Qian Wang Hairong Qi FedML 62 785 0 03 Dec 2018
Tight Dimension Independent Lower Bound on the Expected Convergence Rate for Diminishing Step Sizes in SGD Phuong Ha Nguyen Lam M. Nguyen Marten van Dijk LRM 44 31 0 10 Oct 2018
Differentially-Private "Draw and Discard" Machine Learning Vasyl Pihur Aleksandra Korolova Frederick Liu Subhash Sankuratripati M. Yung Dachuan Huang Ruogu Zeng FedML 45 39 0 11 Jul 2018
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 220 1,700 0 14 Apr 2018
The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks Nicholas Carlini Chang-rui Liu Ulfar Erlingsson Jernej Kos D. Song 118 1,137 0 22 Feb 2018
SGD and Hogwild! Convergence Without the Bounded Gradients Assumption Lam M. Nguyen Phuong Ha Nguyen Marten van Dijk Peter Richtárik K. Scheinberg Martin Takáč 66 227 0 11 Feb 2018
Improved asynchronous parallel optimization analysis for stochastic incremental methods Rémi Leblond Fabian Pedregosa Simon Lacoste-Julien 49 70 0 11 Jan 2018
Differentially Private Federated Learning: A Client Level Perspective Robin C. Geyer T. Klein Moin Nabi FedML 90 1,293 0 20 Dec 2017
Collecting Telemetry Data Privately Bolin Ding Janardhan Kulkarni Sergey Yekhanin 46 682 0 05 Dec 2017
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning Briland Hitaj G. Ateniese Fernando Perez-Cruz FedML 109 1,399 0 24 Feb 2017
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 175 6,101 0 01 Jul 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 276 17,399 0 17 Feb 2016