Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees

25 February 2020

Papers citing "Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees"

34 / 34 papers shown

Title
Privacy Preserving Machine Learning Model Personalization through Federated Personalized Learning Md. Tanzib Hosain Asif Zaman Md. Shahriar Sajid Shadman Sakeeb Khan Shanjida Akter 38 0 0 03 May 2025
On the Byzantine Fault Tolerance of signSGD with Majority Vote Emanuele Mengoli Luzius Moll Virgilio Strozzi El-Mahdi El-Mhamdi AAML FedML 50 0 0 26 Feb 2025
Masked Random Noise for Communication Efficient Federaetd Learning Shiwei Li Yingyi Cheng Haozhao Wang Xing Tang Shijie Xu Weihong Luo Yuhua Li Dugang Liu Xiuqiang He and Ruixuan Li FedML 43 1 0 06 Aug 2024
Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction Wei Jiang Sifan Yang Wenhao Yang Lijun Zhang 21 3 0 01 Jun 2024
Aggressive or Imperceptible, or Both: Network Pruning Assisted Hybrid Byzantines in Federated Learning Emre Ozfatura Kerem Ozfatura Alptekin Kupcu Deniz Gunduz AAML 30 0 0 09 Apr 2024
Privacy Amplification for the Gaussian Mechanism via Bounded Support Shengyuan Hu Saeed Mahloujifar Virginia Smith Kamalika Chaudhuri Chuan Guo FedML 24 1 0 07 Mar 2024
TernaryVote: Differentially Private, Communication Efficient, and Byzantine Resilient Distributed Optimization on Heterogeneous Data Richeng Jin Yujie Gu Kai Yue Xiaofan He Zhaoyang Zhang Huaiyu Dai FedML 20 0 0 16 Feb 2024
SignSGD with Federated Defense: Harnessing Adversarial Attacks through Gradient Sign Decoding Chanho Park Namyoon Lee FedML AAML 22 1 0 02 Feb 2024
Convergence of Sign-based Random Reshuffling Algorithms for Nonconvex Optimization Zhen Qin Zhishuai Liu Pan Xu 18 1 0 24 Oct 2023
Rethinking SIGN Training: Provable Nonconvex Acceleration without First- and Second-Order Gradient Lipschitz Tao Sun Congliang Chen Peng Qiao Li Shen Xinwang Liu Dongsheng Li 26 3 0 23 Oct 2023
Privacy Preserving Federated Learning with Convolutional Variational Bottlenecks Daniel Scheliga Patrick Mäder M. Seeland FedML AAML 18 5 0 08 Sep 2023
Binary Federated Learning with Client-Level Differential Privacy Lumin Liu Jun Zhang Shenghui Song Khaled B. Letaief FedML 13 2 0 07 Aug 2023
Online Learning with Adversaries: A Differential-Inclusion Analysis Swetha Ganesh Alexandre Reiffers Gugan Thoppe FedML 29 3 0 04 Apr 2023
Byzantine-Resilient Federated Learning at Edge Youming Tao Sijia Cui Wenlu Xu Haofei Yin Dongxiao Yu W. Liang Xiuzhen Cheng FedML 15 19 0 18 Mar 2023
Magnitude Matters: Fixing SIGNSGD Through Magnitude-Aware Sparsification in the Presence of Data Heterogeneity Richeng Jin Xiaofan He C. Zhong Zhaoyang Zhang Tony Q. S. Quek H. Dai FedML 21 1 0 19 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 11 2 0 19 Feb 2023
$z$ -SignFedAvg: A Unified Stochastic Sign-based Compression for Federated Learning Zhiwei Tang Yanmeng Wang Tsung-Hui Chang FedML 11 14 0 06 Feb 2023
DoCoFL: Downlink Compression for Cross-Device Federated Learning Ron Dorfman S. Vargaftik Y. Ben-Itzhak Kfir Y. Levy FedML 16 18 0 01 Feb 2023
Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression Xiaoyun Li Ping Li FedML 24 4 0 25 Nov 2022
Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design Chuan Guo Kamalika Chaudhuri Pierre Stock Michael G. Rabbat FedML 17 7 0 08 Nov 2022
Federated Learning and Meta Learning: Approaches, Applications, and Directions Xiaonan Liu Yansha Deng Arumugam Nallanathan M. Bennis 46 32 0 24 Oct 2022
ScionFL: Efficient and Robust Secure Quantized Aggregation Y. Ben-Itzhak Helen Mollering Benny Pinkas T. Schneider Ajith Suresh Oleksandr Tkachenko S. Vargaftik Christian Weinert Hossein Yalame Avishay Yanai 19 6 0 13 Oct 2022
Distributed Non-Convex Optimization with One-Bit Compressors on Heterogeneous Data: Efficient and Resilient Algorithms Ming Xiang Lili Su FedML 16 2 0 03 Oct 2022
A Secure Federated Learning Framework for Residential Short Term Load Forecasting Muhammad Akbar Husnoo A. Anwar N. Hosseinzadeh S. Islam A. N. Mahmood R. Doss 54 33 0 29 Sep 2022
Detection and Mitigation of Byzantine Attacks in Distributed Training Konstantinos Konstantinidis Namrata Vaswani Aditya Ramamoorthy AAML 18 0 0 17 Aug 2022
Practical Vertical Federated Learning with Unsupervised Representation Learning Zhaomin Wu Q. Li Bingsheng He FedML 22 36 0 13 Aug 2022
Towards Efficient Communications in Federated Learning: A Contemporary Survey Zihao Zhao Yuzhu Mao Yang Liu Linqi Song Ouyang Ye Xinlei Chen Wenbo Ding FedML 43 59 0 02 Aug 2022
Communication-Efficient Federated Learning With Data and Client Heterogeneity Hossein Zakerinia Shayan Talaei Giorgi Nadiradze Dan Alistarh FedML 11 7 0 20 Jun 2022
Byzantine Fault Tolerance in Distributed Machine Learning : a Survey Djamila Bouhata Hamouma Moumen Moumen Hamouma Ahcène Bounceur AI4CE 23 7 0 05 May 2022
Bridging Differential Privacy and Byzantine-Robustness via Model Aggregation Heng Zhu Qing Ling FedML 20 23 0 29 Apr 2022
Privacy-Aware Compression for Federated Data Analysis Kamalika Chaudhuri Chuan Guo Michael G. Rabbat FedML 20 27 0 15 Mar 2022
Trusted AI in Multi-agent Systems: An Overview of Privacy and Security for Distributed Learning Chuan Ma Jun Li Kang Wei Bo Liu Ming Ding Long Yuan Zhu Han H. Vincent Poor 39 42 0 18 Feb 2022
Maximizing Communication Efficiency for Large-scale Training via 0/1 Adam Yucheng Lu Conglong Li Minjia Zhang Christopher De Sa Yuxiong He OffRL AI4CE 14 20 0 12 Feb 2022
Federated Learning via Plurality Vote Kai Yue Richeng Jin Chau-Wai Wong H. Dai FedML 16 8 0 06 Oct 2021