Shuffling Momentum Gradient Algorithm for Convex Optimization

5 March 2024

Papers citing "Shuffling Momentum Gradient Algorithm for Convex Optimization"

11 / 11 papers shown

Title
On the Convergence of mSGD and AdaGrad for Stochastic Optimization Ruinan Jin Yu Xing Xingkang He 42 11 0 26 Jan 2022
SMG: A Shuffling Gradient-Based Method with Momentum Trang H. Tran Lam M. Nguyen Quoc Tran-Dinh 56 21 0 24 Nov 2020
SGD with shuffling: optimal rates without component convexity and large epoch requirements Kwangjun Ahn Chulhee Yun S. Sra 47 66 0 12 Jun 2020
Random Reshuffling: Simple Analysis with Vast Improvements Konstantin Mishchenko Ahmed Khaled Peter Richtárik 62 131 0 10 Jun 2020
A Unified Convergence Analysis for Shuffling-Type Gradient Methods Lam M. Nguyen Quoc Tran-Dinh Dzung Phan Phuong Ha Nguyen Marten van Dijk 83 78 0 19 Feb 2020
SGD without Replacement: Sharper Rates for General Smooth Convex Functions Prateek Jain Dheeraj M. Nagaraj Praneeth Netrapalli 50 87 0 04 Mar 2019
Random Shuffling Beats SGD after Finite Epochs Jeff Z. HaoChen S. Sra 49 98 0 26 Jun 2018
SGDR: Stochastic Gradient Descent with Warm Restarts I. Loshchilov Frank Hutter ODL 288 8,091 0 13 Aug 2016
On the Influence of Momentum Acceleration on Online Learning Kun Yuan Bicheng Ying Ali H. Sayed 57 58 0 14 Mar 2016
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 131 1,823 0 01 Jul 2014
Better Mini-Batch Algorithms via Accelerated Gradient Methods Andrew Cotter Ohad Shamir Nathan Srebro Karthik Sridharan ODL 112 313 0 22 Jun 2011