Federated Learning with Compression: Unified Analysis and Sharp Guarantees

2 July 2020

Farzin Haddadpour

Mohammad Mahdi Kamani

Papers citing "Federated Learning with Compression: Unified Analysis and Sharp Guarantees"

50 / 151 papers shown

Title
TACO: Tackling Over-correction in Federated Learning with Tailored Adaptive Correction Weijie Liu Ziwei Zhan Carlee Joe-Wong Edith Ngai Jingpu Duan Deke Guo Xu Chen Xiaotian Zhang FedML 53 0 0 24 Apr 2025
Communication Efficient Federated Learning with Linear Convergence on Heterogeneous Data Jie Liu Yishuo Wang FedML 75 0 0 20 Mar 2025
Layer-wise Update Aggregation with Recycling for Communication-Efficient Federated Learning Jisoo Kim Sungmin Kang Sunwoo Lee FedML 47 0 0 14 Mar 2025
Federated Learning for Diffusion Models Zihao Peng Xijun Wang Shengbo Chen Hong Rao Cong Shen DiffM FedML 53 0 0 09 Mar 2025
Federated Conversational Recommender System Allen Lin Jianling Wang Ziwei Zhu James Caverlee FedML 31 0 0 02 Mar 2025
On the Byzantine Fault Tolerance of signSGD with Majority Vote Emanuele Mengoli Luzius Moll Virgilio Strozzi El-Mahdi El-Mhamdi AAML FedML 60 0 0 26 Feb 2025
Addressing Label Shift in Distributed Learning via Entropy Regularization Zhiyuan Wu Changkyu Choi Xiangcheng Cao V. Cevher Ali Ramezani-Kebrya 81 0 0 04 Feb 2025
Characterizing the Accuracy-Communication-Privacy Trade-off in Distributed Stochastic Convex Optimization Sudeep Salgia Nikola Pavlovic Yuejie Chi Qing Zhao 41 0 0 06 Jan 2025
MARINA-P: Superior Performance in Non-smooth Federated Optimization with Adaptive Stepsizes Igor Sokolov Peter Richtárik 77 1 0 22 Dec 2024
Non-Convex Optimization in Federated Learning via Variance Reduction and Adaptive Learning Dipanwita Thakur Antonella Guzzo Giancarlo Fortino Sajal K. Das FedML 75 0 0 16 Dec 2024
Sketched Adaptive Federated Deep Learning: A Sharp Convergence Analysis Zhijie Chen Qiaobo Li A. Banerjee FedML 35 0 0 11 Nov 2024
DPFedBank: Crafting a Privacy-Preserving Federated Learning Framework for Financial Institutions with Policy Pillars Peilin He Chenkai Lin Isabella Montoya 17 0 0 17 Oct 2024
Unity is Power: Semi-Asynchronous Collaborative Training of Large-Scale Models with Structured Pruning in Resource-Limited Clients Yan Li Mingyi Li Xiao Zhang Guangwei Xu Feng Chen Yuan Yuan Yifei Zou Mengying Zhao Jianbo Lu Dongxiao Yu 28 0 0 11 Oct 2024
Evolving Topics in Federated Learning: Trends, and Emerging Directions for IS Md Raihan Uddin Gauri Shankar Saddam Hossain Mukta Prabhat Kumar Najmul Islam FedML 31 0 0 24 Sep 2024
Green Federated Learning: A new era of Green Aware AI Dipanwita Thakur Antonella Guzzo Giancarlo Fortino Francesco Piccialli AI4CE 48 4 0 19 Sep 2024
Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework Zilinghan Li Shilan He Ze Yang Minseok Ryu Kibaek Kim Ravi K. Madduri FedML 55 5 0 17 Sep 2024
Bandwidth-Aware and Overlap-Weighted Compression for Communication-Efficient Federated Learning Zichen Tang Junlin Huang Rudan Yan Yuxin Wang Zhenheng Tang S. Shi Amelie Chi Zhou Xiaowen Chu FedML 50 2 0 27 Aug 2024
Theoretical Analysis of Privacy Leakage in Trustworthy Federated Learning: A Perspective from Linear Algebra and Optimization Theory Xiaojin Zhang Wei Chen FedML 31 0 0 23 Jul 2024
FedAQ: Communication-Efficient Federated Edge Learning via Joint Uplink and Downlink Adaptive Quantization Linping Qu Shenghui Song Chi-Ying Tsui MQ FedML 18 3 0 26 Jun 2024
Communication-efficient Vertical Federated Learning via Compressed Error Feedback Pedro Valdeira João Xavier Cláudia Soares Yuejie Chi FedML 42 4 0 20 Jun 2024
Fed-Sophia: A Communication-Efficient Second-Order Federated Learning Algorithm Ahmed Elbakary Chaouki Ben Issaid Mohammad Shehab Karim G. Seddik Tamer A. ElBatt Mehdi Bennis 39 2 0 10 Jun 2024
Exploring the Practicality of Federated Learning: A Survey Towards the Communication Perspective Khiem H. Le Nhan Luong-Ha Manh Nguyen-Duc Danh Le-Phuoc Cuong D. Do Kok-Seng Wong FedML 29 1 0 30 May 2024
Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization Zhe Li Bicheng Ying Zidong Liu Haibo Yang Haibo Yang FedML 59 3 0 24 May 2024
Dealing Doubt: Unveiling Threat Models in Gradient Inversion Attacks under Federated Learning, A Survey and Taxonomy Yichuan Shi Olivera Kotevska Viktor Reshniak Abhishek Singh Ramesh Raskar AAML 43 1 0 16 May 2024
Robust Decentralized Learning with Local Updates and Gradient Tracking Sajjad Ghiasvand Amirhossein Reisizadeh Mahnoosh Alizadeh Ramtin Pedarsani 39 3 0 02 May 2024
The Effectiveness of Local Updates for Decentralized Learning under Data Heterogeneity Tongle Wu Ying Sun 36 0 0 23 Mar 2024
Distributed Learning based on 1-Bit Gradient Coding in the Presence of Stragglers Chengxi Li Mikael Skoglund 44 3 0 19 Mar 2024
FedComLoc: Communication-Efficient Distributed Training of Sparse and Quantized Models Kai Yi Georg Meinhardt Laurent Condat Peter Richtárik FedML 37 6 0 14 Mar 2024
LoCoDL: Communication-Efficient Distributed Learning with Local Training and Compression Laurent Condat A. Maranjyan Peter Richtárik 39 3 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
FedMIA: An Effective Membership Inference Attack Exploiting "All for One" Principle in Federated Learning Gongxi Zhu Donghao Li Hanlin Gu Yuxing Han Yuan Yao Lixin Fan 39 2 0 09 Feb 2024
Federated learning with distributed fixed design quantum chips and quantum channels Ammar Daskin FedML 22 0 0 24 Jan 2024
Security and Privacy Issues and Solutions in Federated Learning for Digital Healthcare Hyejun Jeong Tai-Myung Chung FedML 19 1 0 16 Jan 2024
Relaxed Contrastive Learning for Federated Learning Seonguk Seo Jinkyu Kim Geeho Kim Bohyung Han FedML 42 8 0 10 Jan 2024
FedMS: Federated Learning with Mixture of Sparsely Activated Foundations Models Panlong Wu Kangshuo Li Ting Wang Fangxin Wang FedML MoE 17 3 0 26 Dec 2023
Mixed-Precision Quantization for Federated Learning on Resource-Constrained Heterogeneous Devices Huancheng Chen H. Vikalo FedML MQ 16 7 0 29 Nov 2023
FBChain: A Blockchain-based Federated Learning Model with Efficiency and Secure Communication Yang Li Chunhe Xia Wei Liu 37 0 0 21 Nov 2023
Federated Learning with Manifold Regularization and Normalized Update Reaggregation Xuming An Li Shen Han Hu Yong Luo FedML 36 4 0 10 Nov 2023
Distributed Personalized Empirical Risk Minimization Yuyang Deng Mohammad Mahdi Kamani Pouria Mahdavinia M. Mahdavi 31 4 0 26 Oct 2023
Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates Ahmad Rammal Kaja Gruntkowska Nikita Fedin Eduard A. Gorbunov Peter Richtárik 45 5 0 15 Oct 2023
FLrce: Resource-Efficient Federated Learning with Early-Stopping Strategy Ziru Niu Senior Member Ieee Hai Dong •. A. K. Qin Senior Member Ieee Tao Gu 25 4 0 15 Oct 2023
Federated Meta-Learning for Few-Shot Fault Diagnosis with Representation Encoding Jixuan Cui Jun Li Zhen Mei Kang Wei Sha Wei Ming Ding Wen Chen Song Guo FedML 25 7 0 13 Oct 2023
Revisiting Decentralized ProxSkip: Achieving Linear Speedup Luyao Guo Sulaiman A. Alghunaim Kun Yuan Laurent Condat Jinde Cao FedML 36 1 0 12 Oct 2023
Federated Learning for Computer Vision Yassine Himeur Iraklis Varlamis Hamza Kheddar Abbes Amira Shadi Atalla Yashbir Singh F. Bensaali W. Mansoor FedML 26 20 0 24 Aug 2023
Joint Power Control and Data Size Selection for Over-the-Air Computation Aided Federated Learning Xuming An Rongfei Fan Shiyuan Zuo Han Hu Haiyang Jiang Ningsong Zhang FedML 30 0 0 17 Aug 2023
Stochastic Controlled Averaging for Federated Learning with Communication Compression Xinmeng Huang Ping Li Xiaoyun Li 37 195 0 16 Aug 2023
Communication-Efficient Federated Learning over Capacity-Limited Wireless Networks Jae-Bok Yun Yong-Nam Oh Yo-Seb Jeon H. Vincent Poor 20 2 0 20 Jul 2023
Momentum Benefits Non-IID Federated Learning Simply and Provably Ziheng Cheng Xinmeng Huang Pengfei Wu Kun Yuan FedML 29 16 0 28 Jun 2023
Randomized Quantization is All You Need for Differential Privacy in Federated Learning Yeojoon Youn Zihao Hu Juba Ziani Jacob D. Abernethy FedML 19 21 0 20 Jun 2023
Improving Accelerated Federated Learning with Compression and Importance Sampling Michal Grudzieñ Grigory Malinovsky Peter Richtárik FedML 35 8 0 05 Jun 2023