The Min-Max Complexity of Distributed Stochastic Convex Optimization
with Intermittent Communication

The Min-Max Complexity of Distributed Stochastic Convex Optimization with Intermittent Communication

2 February 2021

Blake E. Woodworth

Papers citing "The Min-Max Complexity of Distributed Stochastic Convex Optimization with Intermittent Communication"

12 / 12 papers shown

Title
The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication Kumar Kshitij Patel Margalit Glasgow Ali Zindari Lingxiao Wang Sebastian U. Stich Ziheng Cheng Nirmit Joshi Nathan Srebro 48 6 0 19 May 2024
Distributed Extra-gradient with Optimal Complexity and Communication Guarantees Ali Ramezani-Kebrya Kimon Antonakopoulos Igor Krawczuk Justin Deschenaux V. Cevher 36 2 0 17 Aug 2023
DualFL: A Duality-based Federated Learning Algorithm with Communication Acceleration in the General Convex Regime Jongho Park Jinchao Xu FedML 60 1 0 17 May 2023
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities Aleksandr Beznosikov Martin Takáč Alexander Gasnikov 29 10 0 15 Feb 2023
ReSQueing Parallel and Private Stochastic Convex Optimization Y. Carmon A. Jambulapati Yujia Jin Y. Lee Daogao Liu Aaron Sidford Kevin Tian FedML 22 12 0 01 Jan 2023
Federated Optimization Algorithms with Random Reshuffling and Gradient Compression Abdurakhmon Sadiev Grigory Malinovsky Eduard A. Gorbunov Igor Sokolov Ahmed Khaled Konstantin Burlachenko Peter Richtárik FedML 16 21 0 14 Jun 2022
Efficient Convex Optimization Requires Superlinear Memory A. Marsden Vatsal Sharan Aaron Sidford Gregory Valiant 29 14 0 29 Mar 2022
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
FedChain: Chained Algorithms for Near-Optimal Communication Cost in Federated Learning Charlie Hou K. K. Thekumparampil Giulia Fanti Sewoong Oh FedML 30 14 0 16 Aug 2021
Accelerated, Optimal, and Parallel: Some Results on Model-Based Stochastic Optimization Karan N. Chadha Gary Cheng John C. Duchi 49 16 0 07 Jan 2021
New Convergence Aspects of Stochastic Gradient Algorithms Lam M. Nguyen Phuong Ha Nguyen Peter Richtárik K. Scheinberg Martin Takáč Marten van Dijk 23 66 0 10 Nov 2018
Optimal Distributed Online Prediction using Mini-Batches O. Dekel Ran Gilad-Bachrach Ohad Shamir Lin Xiao 177 683 0 07 Dec 2010