Parallelization does not Accelerate Convex Optimization: Adaptivity Lower Bounds for Non-smooth Convex Minimization

12 August 2018

Papers citing "Parallelization does not Accelerate Convex Optimization: Adaptivity Lower Bounds for Non-smooth Convex Minimization"

10 / 10 papers shown

Title
Memory-Query Tradeoffs for Randomized Convex Optimization Xinyu Chen Binghui Peng 36 6 0 21 Jun 2023
Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression Yutong He Xinmeng Huang Yiming Chen W. Yin Kun Yuan 28 7 0 12 May 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
Efficient Convex Optimization Requires Superlinear Memory A. Marsden Vatsal Sharan Aaron Sidford Gregory Valiant 29 14 0 29 Mar 2022
Lower Bounds and Optimal Algorithms for Personalized Federated Learning Filip Hanzely Slavomír Hanzely Samuel Horváth Peter Richtárik FedML 41 186 0 05 Oct 2020
Optimal Complexity in Decentralized Training Yucheng Lu Christopher De Sa 38 71 0 15 Jun 2020
Complexity of Highly Parallel Non-Smooth Convex Optimization Sébastien Bubeck Qijia Jiang Y. Lee Yuanzhi Li Aaron Sidford 23 55 0 25 Jun 2019
Lower Bounds for Parallel and Randomized Convex Optimization Jelena Diakonikolas Cristóbal Guzmán 33 44 0 05 Nov 2018
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 101 570 0 08 Dec 2012
Optimal Distributed Online Prediction using Mini-Batches O. Dekel Ran Gilad-Bachrach Ohad Shamir Lin Xiao 177 683 0 07 Dec 2010