Local SGD Converges Fast and Communicates Little

24 May 2018

Papers citing "Local SGD Converges Fast and Communicates Little"

50 / 629 papers shown

Title
Efficient Algorithms for Federated Saddle Point Optimization Charlie Hou K. K. Thekumparampil Giulia Fanti Sewoong Oh FedML 18 23 0 12 Feb 2021
Stragglers Are Not Disaster: A Hybrid Federated Learning Algorithm with Delayed Gradients Xingyu Li Zhe Qu Bo Tang Zhuo Lu FedML 65 31 0 12 Feb 2021
Energy-Harvesting Distributed Machine Learning Başak Güler Aylin Yener FedML 21 15 0 10 Feb 2021
Local and Global Uniform Convexity Conditions Thomas Kerdreux Alexandre d’Aspremont S. Pokutta 10 12 0 09 Feb 2021
Federated Deep AUC Maximization for Heterogeneous Data with a Constant Communication Complexity Zhuoning Yuan Zhishuai Guo Yi Tian Xu Yiming Ying Tianbao Yang FedML 13 35 0 09 Feb 2021
Adaptive Quantization of Model Updates for Communication-Efficient Federated Learning Divyansh Jhunjhunwala Advait Gadhikar Gauri Joshi Yonina C. Eldar FedML MQ 9 107 0 08 Feb 2021
Coordinating Momenta for Cross-silo Federated Learning An Xu Heng-Chiao Huang FedML 13 19 0 08 Feb 2021
Multi-Tier Federated Learning for Vertically Partitioned Data Anirban Das S. Patterson FedML 13 16 0 06 Feb 2021
Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning Tomoya Murata Taiji Suzuki FedML 16 50 0 05 Feb 2021
1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed Hanlin Tang Shaoduo Gan A. A. Awan Samyam Rajbhandari Conglong Li Xiangru Lian Ji Liu Ce Zhang Yuxiong He AI4CE 37 84 0 04 Feb 2021
A Bayesian Federated Learning Framework with Online Laplace Approximation Liang Liu Xi Jiang Feng Zheng Hong Chen Guo-Jun Qi Heng-Chiao Huang Ling Shao FedML 43 53 0 03 Feb 2021
Truly Sparse Neural Networks at Scale Selima Curci D. Mocanu Mykola Pechenizkiy 25 19 0 02 Feb 2021
The Min-Max Complexity of Distributed Stochastic Convex Optimization with Intermittent Communication Blake E. Woodworth Brian Bullins Ohad Shamir Nathan Srebro 11 46 0 02 Feb 2021
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning Haibo Yang Minghong Fang Jia Liu FedML 11 249 0 27 Jan 2021
Auto-weighted Robust Federated Learning with Corrupted Data Sources Shenghui Li Edith C. H. Ngai Fanghua Ye Thiemo Voigt FedML 16 28 0 14 Jan 2021
Federated Learning over Noisy Channels: Convergence Analysis and Design Examples Xizixiang Wei Cong Shen FedML 36 15 0 06 Jan 2021
Delayed Projection Techniques for Linearly Constrained Problems: Convergence Rates, Acceleration, and Applications Xiang Li Zhihua Zhang 22 4 0 05 Jan 2021
CADA: Communication-Adaptive Distributed Adam Tianyi Chen Ziye Guo Yuejiao Sun W. Yin ODL 6 24 0 31 Dec 2020
Straggler-Resilient Federated Learning: Leveraging the Interplay Between Statistical Accuracy and System Heterogeneity Amirhossein Reisizadeh Isidoros Tziotis Hamed Hassani Aryan Mokhtari Ramtin Pedarsani FedML 164 98 0 28 Dec 2020
Cost-Effective Federated Learning Design Bing Luo Xiang Li Shiqiang Wang Jianwei Huang Leandros Tassiulas FedML 6 177 0 15 Dec 2020
Bandit-based Communication-Efficient Client Selection Strategies for Federated Learning Yae Jee Cho Samarth Gupta Gauri Joshi Osman Yağan FedML 8 67 0 14 Dec 2020
Federated Learning under Importance Sampling Elsa Rizk Stefan Vlaski A. H. Sayed FedML 11 51 0 14 Dec 2020
DONE: Distributed Approximate Newton-type Method for Federated Edge Learning Canh T. Dinh N. H. Tran Tuan Dung Nguyen Wei Bao A. R. Balef B. Zhou Albert Y. Zomaya FedML 16 15 0 10 Dec 2020
Federated Learning in Unreliable and Resource-Constrained Cellular Wireless Networks M. Salehi E. Hossain FedML 49 81 0 09 Dec 2020
Faster Non-Convex Federated Learning via Global and Local Momentum Rudrajit Das Anish Acharya Abolfazl Hashemi Sujay Sanghavi Inderjit S. Dhillon Ufuk Topcu FedML 27 82 0 07 Dec 2020
Design and Analysis of Uplink and Downlink Communications for Federated Learning Sihui Zheng Cong Shen Xiang Chen 28 139 0 07 Dec 2020
Second-Order Guarantees in Federated Learning Stefan Vlaski Elsa Rizk A. H. Sayed FedML 12 7 0 02 Dec 2020
Federated Composite Optimization Honglin Yuan Manzil Zaheer Sashank J. Reddi FedML 24 57 0 17 Nov 2020
FedRec: Federated Learning of Universal Receivers over Fading Channels Mahdi Boloursaz Mashhadi Nir Shlezinger Yonina C. Eldar Deniz Gunduz FedML 6 15 0 14 Nov 2020
Distributed Sparse SGD with Majority Voting Kerem Ozfatura Emre Ozfatura Deniz Gunduz FedML 38 4 0 12 Nov 2020
Adaptive Federated Dropout: Improving Communication Efficiency and Generalization for Federated Learning Nader Bouacida Jiahui Hou H. Zang Xin Liu FedML 9 75 0 08 Nov 2020
Communication-efficient Decentralized Local SGD over Undirected Networks Tiancheng Qin S. Rasoul Etesami César A. Uribe FedML 14 14 0 06 Nov 2020
FederBoost: Private Federated Learning for GBDT Zhihua Tian Rui Zhang Xiaoyang Hou Jian-wei Liu K. Ren Jian Liu Kui Ren FedML AI4CE 39 66 0 05 Nov 2020
LQR with Tracking: A Zeroth-order Approach and Its Global Convergence Zhaolin Ren Aoxiao Zhong Na Li 9 3 0 03 Nov 2020
Local SGD: Unified Theory and New Efficient Methods Eduard A. Gorbunov Filip Hanzely Peter Richtárik FedML 28 108 0 03 Nov 2020
Accordion: Adaptive Gradient Communication via Critical Learning Regime Identification Saurabh Agarwal Hongyi Wang Kangwook Lee Shivaram Venkataraman Dimitris Papailiopoulos 34 25 0 29 Oct 2020
Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes Marten van Dijk Nhuong V. Nguyen Toan N. Nguyen Lam M. Nguyen Quoc Tran-Dinh Phuong Ha Nguyen FedML 34 10 0 27 Oct 2020
Optimal Client Sampling for Federated Learning Wenlin Chen Samuel Horváth Peter Richtárik FedML 19 190 0 26 Oct 2020
Demystifying Why Local Aggregation Helps: Convergence Analysis of Hierarchical SGD Jiayi Wang Shiqiang Wang Rong-Rong Chen Mingyue Ji FedML 28 51 0 24 Oct 2020
Linearly Converging Error Compensated SGD Eduard A. Gorbunov D. Kovalev Dmitry Makarenko Peter Richtárik 163 77 0 23 Oct 2020
Hierarchical Federated Learning through LAN-WAN Orchestration Jinliang Yuan Mengwei Xu Xiao Ma Ao Zhou Xuanzhe Liu Shangguang Wang FedML 14 38 0 22 Oct 2020
Towards Tight Communication Lower Bounds for Distributed Optimisation Dan Alistarh Janne H. Korhonen FedML 17 6 0 16 Oct 2020
Optimal Gradient Compression for Distributed and Federated Learning Alyazeed Albasyoni M. Safaryan Laurent Condat Peter Richtárik FedML 6 60 0 07 Oct 2020
A Closer Look at Codistillation for Distributed Training Shagun Sodhani Olivier Delalleau Mahmoud Assran Koustuv Sinha Nicolas Ballas Michael G. Rabbat 19 8 0 06 Oct 2020
Client Selection in Federated Learning: Convergence Analysis and Power-of-Choice Selection Strategies Yae Jee Cho Jianyu Wang Gauri Joshi FedML 33 400 0 03 Oct 2020
Over-the-Air Federated Learning from Heterogeneous Data Tomer Sery Nir Shlezinger Kobi Cohen Yonina C. Eldar FedML 9 194 0 27 Sep 2020
Adversarial Robustness through Bias Variance Decomposition: A New Perspective for Federated Learning Yao Zhou Jun Wu Haixun Wang Jingrui He AAML FedML 18 26 0 18 Sep 2020
HPSGD: Hierarchical Parallel SGD With Stale Gradients Featuring Yuhao Zhou Qing Ye Hailun Zhang Jiancheng Lv 3DH 12 0 0 06 Sep 2020
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning Hong-You Chen Wei-Lun Chao FedML 14 255 0 04 Sep 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 19 0 0 26 Aug 2020