SCAFFOLD: Stochastic Controlled Averaging for Federated Learning

14 October 2019

Sai Praneeth Karimireddy

Papers citing "SCAFFOLD: Stochastic Controlled Averaging for Federated Learning"

37 / 87 papers shown

Title
Federated Learning on Non-IID Data Silos: An Experimental Study Yue Liu Yiqun Diao Quan Chen Bingsheng He FedML OOD 101 950 0 03 Feb 2021
Bandwidth Allocation for Multiple Federated Learning Services in Wireless Edge Networks Jie Xu Heqiang Wang Lixing Chen FedML 56 43 0 10 Jan 2021
Optimising cost vs accuracy of decentralised analytics in fog computing environments Lorenzo Valerio A. Passarella M. Conti 35 1 0 09 Dec 2020
Local SGD: Unified Theory and New Efficient Methods Eduard A. Gorbunov Filip Hanzely Peter Richtárik FedML 35 109 0 03 Nov 2020
Optimal Client Sampling for Federated Learning Wenlin Chen Samuel Horváth Peter Richtárik FedML 42 191 0 26 Oct 2020
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms Maruan Al-Shedivat Jennifer Gillenwater Eric P. Xing Afshin Rostamizadeh FedML 19 109 0 11 Oct 2020
Client Selection in Federated Learning: Convergence Analysis and Power-of-Choice Selection Strategies Yae Jee Cho Jianyu Wang Gauri Joshi FedML 47 401 0 03 Oct 2020
Practical One-Shot Federated Learning for Cross-Silo Setting Qinbin Li Bingsheng He D. Song FedML 18 114 0 02 Oct 2020
Distilled One-Shot Federated Learning Yanlin Zhou George Pu Xiyao Ma Xiaolin Li D. Wu FedML DD 51 158 0 17 Sep 2020
Effective Federated Adaptive Gradient Methods with Non-IID Decentralized Data Qianqian Tong Guannan Liang J. Bi FedML 41 27 0 14 Sep 2020
On Communication Compression for Distributed Optimization on Heterogeneous Data Sebastian U. Stich 50 23 0 04 Sep 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 34 0 0 26 Aug 2020
PowerGossip: Practical Low-Rank Communication Compression in Decentralized Deep Learning Thijs Vogels Sai Praneeth Karimireddy Martin Jaggi FedML 11 54 0 04 Aug 2020
Fast-Convergent Federated Learning Hung T. Nguyen Vikash Sehwag Seyyedali Hosseinalipour Christopher G. Brinton M. Chiang H. Vincent Poor FedML 26 192 0 26 Jul 2020
FetchSGD: Communication-Efficient Federated Learning with Sketching D. Rothchild Ashwinee Panda Enayat Ullah Nikita Ivkin Ion Stoica Vladimir Braverman Joseph E. Gonzalez Raman Arora FedML 28 361 0 15 Jul 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang Qinghua Liu Hao Liang Gauri Joshi H. Vincent Poor MoMe FedML 16 1,297 0 15 Jul 2020
Personalized Cross-Silo Federated Learning on Non-IID Data Yutao Huang Lingyang Chu Zirui Zhou Lanjun Wang Jiangchuan Liu J. Pei Yong Zhang FedML 20 591 0 07 Jul 2020
Federated Learning with Compression: Unified Analysis and Sharp Guarantees Farzin Haddadpour Mohammad Mahdi Kamani Aryan Mokhtari M. Mahdavi FedML 39 273 0 02 Jul 2020
Robust Federated Learning: The Case of Affine Distribution Shifts Amirhossein Reisizadeh Farzan Farnia Ramtin Pedarsani Ali Jadbabaie FedML OOD 32 162 0 16 Jun 2020
Minibatch vs Local SGD for Heterogeneous Distributed Learning Blake E. Woodworth Kumar Kshitij Patel Nathan Srebro FedML 22 199 0 08 Jun 2020
Adaptive Personalized Federated Learning Yuyang Deng Mohammad Mahdi Kamani M. Mahdavi FedML 212 60 0 30 Mar 2020
Federated Residual Learning Alekh Agarwal John Langford Chen-Yu Wei FedML 22 40 0 28 Mar 2020
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates Anastasia Koloskova Nicolas Loizou Sadra Boreiri Martin Jaggi Sebastian U. Stich FedML 41 493 0 23 Mar 2020
Federated Continual Learning with Weighted Inter-client Transfer Jaehong Yoon Wonyoung Jeong Giwoong Lee Eunho Yang Sung Ju Hwang FedML 40 199 0 06 Mar 2020
Adaptive Federated Optimization Sashank J. Reddi Zachary B. Charles Manzil Zaheer Zachary Garrett Keith Rush Jakub Konecný Sanjiv Kumar H. B. McMahan FedML 20 1,391 0 29 Feb 2020
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization Zhize Li D. Kovalev Xun Qian Peter Richtárik FedML AI4CE 29 135 0 26 Feb 2020
Three Approaches for Personalization with Applications to Federated Learning Yishay Mansour M. Mohri Jae Hun Ro A. Suresh FedML 45 565 0 25 Feb 2020
Uncertainty Principle for Communication Compression in Distributed and Federated Learning and the Search for an Optimal Compressor M. Safaryan Egor Shulgin Peter Richtárik 32 60 0 20 Feb 2020
Personalized Federated Learning: A Meta-Learning Approach Alireza Fallah Aryan Mokhtari Asuman Ozdaglar FedML 36 561 0 19 Feb 2020
Is Local SGD Better than Minibatch SGD? Blake E. Woodworth Kumar Kshitij Patel Sebastian U. Stich Zhen Dai Brian Bullins H. B. McMahan Ohad Shamir Nathan Srebro FedML 34 253 0 18 Feb 2020
FedDANE: A Federated Newton-Type Method Tian Li Anit Kumar Sahu Manzil Zaheer Maziar Sanjabi Ameet Talwalkar Virginia Smith FedML 18 155 0 07 Jan 2020
Energy Efficient Federated Learning Over Wireless Communication Networks Zhaohui Yang Mingzhe Chen Walid Saad Choong Seon Hong M. Shikh-Bahaei 30 681 0 06 Nov 2019
On the Convergence of Local Descent Methods in Federated Learning Farzin Haddadpour M. Mahdavi FedML 19 266 0 31 Oct 2019
The Non-IID Data Quagmire of Decentralized Machine Learning Kevin Hsieh Amar Phanishayee O. Mutlu Phillip B. Gibbons 6 558 0 01 Oct 2019
The Error-Feedback Framework: Better Rates for SGD with Delayed Gradients and Compressed Communication Sebastian U. Stich Sai Praneeth Karimireddy FedML 22 20 0 11 Sep 2019
Unified Optimal Analysis of the (Stochastic) Gradient Method Sebastian U. Stich 26 112 0 09 Jul 2019
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 144 1,687 0 14 Apr 2018