AIDE: Fast and Communication Efficient Distributed Optimization

24 August 2016

Papers citing "AIDE: Fast and Communication Efficient Distributed Optimization"

31 / 31 papers shown

Title
Flattened one-bit stochastic gradient descent: compressed distributed optimization with controlled variance A. Stollenwerk Laurent Jacques FedML 23 0 0 17 May 2024
Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis Dachao Lin Yuze Han Haishan Ye Zhihua Zhang 22 11 0 15 Apr 2023
FedSSO: A Federated Server-Side Second-Order Optimization Algorithm Xinteng Ma Renyi Bao Jinpeng Jiang Yang Liu Arthur Jiang Junhua Yan Xin Liu Zhisong Pan FedML 32 6 0 20 Jun 2022
SHED: A Newton-type algorithm for federated learning based on incremental Hessian eigenvector sharing Nicolò Dal Fabbro S. Dey M. Rossi Luca Schenato FedML 29 14 0 11 Feb 2022
Linear Speedup in Personalized Collaborative Learning El Mahdi Chayti Sai Praneeth Karimireddy Sebastian U. Stich Nicolas Flammarion Martin Jaggi FedML 15 13 0 10 Nov 2021
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning Xun Qian Rustem Islamov M. Safaryan Peter Richtárik FedML 24 23 0 02 Nov 2021
Acceleration in Distributed Optimization under Similarity Helena Lofstrom G. Scutari Tianyue Cao Alexander Gasnikov 21 26 0 24 Oct 2021
A Stochastic Newton Algorithm for Distributed Convex Optimization Brian Bullins Kumar Kshitij Patel Ohad Shamir Nathan Srebro Blake E. Woodworth 28 15 0 07 Oct 2021
Communication Efficiency in Federated Learning: Achievements and Challenges Osama Shahid Seyedamin Pouriyeh R. Parizi Quan Z. Sheng Gautam Srivastava Liang Zhao FedML 40 74 0 23 Jul 2021
FedNL: Making Newton-Type Methods Applicable to Federated Learning M. Safaryan Rustem Islamov Xun Qian Peter Richtárik FedML 33 77 0 05 Jun 2021
Distributed Second Order Methods with Fast Rates and Compressed Communication Rustem Islamov Xun Qian Peter Richtárik 32 51 0 14 Feb 2021
Newton Method over Networks is Fast up to the Statistical Precision Amir Daneshmand G. Scutari Pavel Dvurechensky Alexander Gasnikov 24 21 0 12 Feb 2021
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 20 15 0 10 Dec 2020
Toward Multiple Federated Learning Services Resource Sharing in Mobile Edge Networks Minh N. H. Nguyen N. H. Tran Y. Tun Zhu Han Choong Seon Hong FedML 21 49 0 25 Nov 2020
Sparse sketches with small inversion bias Michal Derezinski Zhenyu Liao Yan Sun Michael W. Mahoney 23 21 0 21 Nov 2020
Local SGD: Unified Theory and New Efficient Methods Eduard A. Gorbunov Filip Hanzely Peter Richtárik FedML 35 109 0 03 Nov 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 32 0 0 26 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
COKE: Communication-Censored Decentralized Kernel Learning Ping Xu Yue Wang Xiang Chen Z. Tian 15 20 0 28 Jan 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
Communication-Efficient Local Decentralized SGD Methods Xiang Li Wenhao Yang Shusen Wang Zhihua Zhang 30 53 0 21 Oct 2019
Overcoming Forgetting in Federated Learning on Non-IID Data N. Shoham Tomer Avidor Aviv Keren Nadav Tal-Israel Daniel Benditkis Liron Mor Yosef Itai Zeitak CLL FedML 23 217 0 17 Oct 2019
On the Convergence of FedAvg on Non-IID Data Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang FedML 64 2,283 0 04 Jul 2019
Natural Compression for Distributed Deep Learning Samuel Horváth Chen-Yu Ho L. Horvath Atal Narayan Sahu Marco Canini Peter Richtárik 21 150 0 27 May 2019
A Distributed Second-Order Algorithm You Can Trust Celestine Mendler-Dünner Aurelien Lucchi Matilde Gargiani An Bian Thomas Hofmann Martin Jaggi 26 32 0 20 Jun 2018
Gradient Sparsification for Communication-Efficient Distributed Optimization Jianqiao Wangni Jialei Wang Ji Liu Tong Zhang 15 522 0 26 Oct 2017
Stochastic Nonconvex Optimization with Large Minibatches Weiran Wang Nathan Srebro 36 26 0 25 Sep 2017
GIANT: Globally Improved Approximate Newton Method for Distributed Optimization Shusen Wang Farbod Roosta-Khorasani Peng Xu Michael W. Mahoney 30 127 0 11 Sep 2017
Memory and Communication Efficient Distributed Stochastic Optimization with Minibatch-Prox Jialei Wang Weiran Wang Nathan Srebro 16 54 0 21 Feb 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 34 4,588 0 18 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 48 1,876 0 08 Oct 2016