cpSGD: Communication-efficient and differentially-private distributed SGD

27 May 2018

Sanjiv Kumar

Papers citing "cpSGD: Communication-efficient and differentially-private distributed SGD"

50 / 238 papers shown

Title
Fast Optimal Locally Private Mean Estimation via Random Projections Hilal Asi Vitaly Feldman Jelani Nelson Huy Le Nguyen Kunal Talwar FedML 45 13 0 07 Jun 2023
FedHC: A Scalable Federated Learning Framework for Heterogeneous and Resource-Constrained Clients Hao Fei Fuxun Yu Yongbo Yu Minjia Zhang Ang Li Xiang Chen FedML 11 2 0 25 May 2023
Differential Privacy with Random Projections and Sign Random Projections P. Li Xiaoyun Li 36 8 0 22 May 2023
Client Selection for Federated Policy Optimization with Environment Heterogeneity Zhijie Xie S. H. Song 27 3 0 18 May 2023
Securing Distributed SGD against Gradient Leakage Threats Wenqi Wei Ling Liu Jingya Zhou Ka-Ho Chow Yanzhao Wu FedML 28 18 0 10 May 2023
FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity Nannan Wu Li Yu Xue Jiang Kwang-Ting Cheng Zengqiang Yan FedML 30 37 0 09 May 2023
FedNC: A Secure and Efficient Federated Learning Method with Network Coding Yuchen Shi Zheqi Zhu Pingyi Fan Khaled B. Letaief Chenghui Peng FedML 23 0 0 05 May 2023
Efficient Federated Learning with Enhanced Privacy via Lottery Ticket Pruning in Edge Computing Yi Shi Kang Wei Li Shen Jun Li Xueqian Wang Bo Yuan Song Guo 44 5 0 02 May 2023
Towards the Flatter Landscape and Better Generalization in Federated Learning under Client-level Differential Privacy Yi Shi Kang Wei Li Shen Yingqi Liu Xueqian Wang Bo Yuan Dacheng Tao FedML 38 2 0 01 May 2023
Killing Two Birds with One Stone: Quantization Achieves Privacy in Distributed Learning Guangfeng Yan Tan Li Kui Wu Linqi Song 28 12 0 26 Apr 2023
A review of distributed statistical inference Yuan Gao Weidong Liu Hansheng Wang Xiaozhou Wang Yibo Yan Riquan Zhang 16 42 0 13 Apr 2023
When approximate design for fast homomorphic computation provides differential privacy guarantees Arnaud Grivet Sébert Martin Zuber Oana Stan Renaud Sirdey Cédric Gouy-Pailler TPM 19 1 0 06 Apr 2023
Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation Wei-Ning Chen Danni Song Ayfer Özgür Peter Kairouz FedML 28 25 0 04 Apr 2023
Make Landscape Flatter in Differentially Private Federated Learning Yi Shi Yingqi Liu Kang Wei Li Shen Xueqian Wang Dacheng Tao FedML 25 54 0 20 Mar 2023
Private Read-Update-Write with Controllable Information Leakage for Storage-Efficient Federated Learning with Top $r$ Sparsification Sajani Vithana S. Ulukus FedML 27 5 0 07 Mar 2023
Differentially Private Distributed Convex Optimization Minseok Ryu Kibaek Kim FedML 25 1 0 28 Feb 2023
Multi-Message Shuffled Privacy in Federated Learning Antonious M. Girgis Suhas Diggavi FedML 28 8 0 22 Feb 2023
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy Yifei Zhang Dun Zeng Jinglong Luo Zenglin Xu Irwin King FedML 84 47 0 21 Feb 2023
Breaking the Communication-Privacy-Accuracy Tradeoff with $f$ -Differential Privacy Richeng Jin Z. Su C. Zhong Zhaoyang Zhang Tony Q.S. Quek H. Dai FedML 29 2 0 19 Feb 2023
On the Privacy-Robustness-Utility Trilemma in Distributed Learning Youssef Allouah R. Guerraoui Nirupam Gupta Rafael Pinot John Stephan FedML 20 21 0 09 Feb 2023
DIFF2: Differential Private Optimization via Gradient Differences for Nonconvex Distributed Learning Tomoya Murata Taiji Suzuki 30 8 0 08 Feb 2023
$z$ -SignFedAvg: A Unified Stochastic Sign-based Compression for Federated Learning Zhiwei Tang Yanmeng Wang Tsung-Hui Chang FedML 21 14 0 06 Feb 2023
M22: A Communication-Efficient Algorithm for Federated Learning Inspired by Rate-Distortion Yangyi Liu Stefano Rini Sadaf Salehkalaibar Jun Chen FedML 21 4 0 23 Jan 2023
Skellam Mixture Mechanism: a Novel Approach to Federated Learning with Differential Privacy Ergute Bao Yizheng Zhu X. Xiao Yifan Yang Beng Chin Ooi B. Tan Khin Mi Mi Aung FedML 31 18 0 08 Dec 2022
Optimal Privacy Preserving for Federated Learning in Mobile Edge Computing Hai M. Nguyen N. Chu Diep N. Nguyen D. Hoang Van-Dinh Nguyen Minh Hoàng Hà E. Dutkiewicz Marwan Krunz FedML 27 1 0 14 Nov 2022
Distributed DP-Helmet: Scalable Differentially Private Non-interactive Averaging of Single Layers Moritz Kirschte Sebastian Meiser Saman Ardalan Esfandiar Mohammadi FedML 34 0 0 03 Nov 2022
Contraction of Locally Differentially Private Mechanisms S. Asoodeh Huanyu Zhang 26 10 0 24 Oct 2022
Federated Learning for Tabular Data: Exploring Potential Risk to Privacy Han Wu Zilong Zhao L. Chen Aad van Moorsel FedML 23 7 0 13 Oct 2022
Over-the-Air Federated Learning with Privacy Protection via Correlated Additive Perturbations Jialing Liao Zheng Chen Erik G. Larsson 25 12 0 05 Oct 2022
Private Read Update Write (PRUW) in Federated Submodel Learning (FSL): Communication Efficient Schemes With and Without Sparsification Sajani Vithana S. Ulukus FedML 20 19 0 09 Sep 2022
Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks Chulin Xie Yunhui Long Pin-Yu Chen Qinbin Li Arash Nourian Sanmi Koyejo Bo Li FedML 43 13 0 08 Sep 2022
Privacy of Autonomous Vehicles: Risks, Protection Methods, and Future Directions Chulin Xie Zhong Cao Yunhui Long Diange Yang Ding Zhao Bo-wen Li 19 4 0 08 Sep 2022
Decentralized Collaborative Learning with Probabilistic Data Protection T. Idé Raymond H. Putra FedML 27 2 0 23 Aug 2022
Quantization enabled Privacy Protection in Decentralized Stochastic Optimization Yongqiang Wang Tamer Basar 19 44 0 07 Aug 2022
How Much Privacy Does Federated Learning with Secure Aggregation Guarantee? A. Elkordy Jiang Zhang Yahya H. Ezzeldin Konstantinos Psounis A. Avestimehr FedML 35 38 0 03 Aug 2022
Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM Chulin Xie Pin-Yu Chen Qinbin Li Arash Nourian Ce Zhang Bo Li FedML 33 16 0 20 Jul 2022
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning Yuanhao Xiong Ruochen Wang Minhao Cheng Felix X. Yu Cho-Jui Hsieh FedML DD 50 82 0 20 Jul 2022
Combined Federated and Split Learning in Edge Computing for Ubiquitous Intelligence in Internet of Things: State of the Art and Future Directions Qiang Duan Shijing Hu Ruijun Deng Zhihui Lu FedML 31 61 0 20 Jul 2022
The Poisson binomial mechanism for secure and private federated learning Wei-Ning Chen Ayfer Özgür Peter Kairouz FedML 16 2 0 09 Jul 2022
Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms Ehsan Hallaji R. Razavi-Far M. Saif AAML FedML 24 13 0 05 Jul 2022
sqSGD: Locally Private and Communication Efficient Federated Learning Yan Feng Tao Xiong Ruofan Wu Lingjuan Lv Leilei Shi FedML 25 2 0 21 Jun 2022
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression Zhize Li Haoyu Zhao Boyue Li Yuejie Chi FedML 32 41 0 20 Jun 2022
Gradient Obfuscation Gives a False Sense of Security in Federated Learning Kai Yue Richeng Jin Chau-Wai Wong D. Baron H. Dai FedML 31 46 0 08 Jun 2022
Group privacy for personalized federated learning Filippo Galli Sayan Biswas Kangsoo Jung Tommaso Cucinotta C. Palamidessi FedML 13 12 0 07 Jun 2022
Private Federated Submodel Learning with Sparsification Sajani Vithana S. Ulukus FedML 26 10 0 31 May 2022
Federated learning: Applications, challenges and future directions Subrato Bharati Hossain Mondal Prajoy Podder V. B. Surya Prasath FedML 39 53 0 18 May 2022
On Distributed Adaptive Optimization with Gradient Compression Xiaoyun Li Belhal Karimi Ping Li 17 25 0 11 May 2022
Protecting Data from all Parties: Combining FHE and DP in Federated Learning Arnaud Grivet Sébert Renaud Sirdey Oana Stan Cédric Gouy-Pailler FedML 18 0 0 09 May 2022
Byzantine Fault Tolerance in Distributed Machine Learning : a Survey Djamila Bouhata Hamouma Moumen Moumen Hamouma Ahcène Bounceur AI4CE 27 7 0 05 May 2022
Optimal Algorithms for Mean Estimation under Local Differential Privacy Hilal Asi Vitaly Feldman Kunal Talwar 40 41 0 05 May 2022