An optimal randomized incremental gradient method

8 July 2015

Papers citing "An optimal randomized incremental gradient method"

35 / 35 papers shown

Title
Dynamic Anisotropic Smoothing for Noisy Derivative-Free Optimization S. Reifenstein T. Leleu Yoshihisa Yamamoto 48 1 0 02 May 2024
A simple uniformly optimal method without line search for convex optimization Tianjiao Li Guanghui Lan 26 20 0 16 Oct 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
Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis Dachao Lin Yuze Han Haishan Ye Zhihua Zhang 25 11 0 15 Apr 2023
A principled framework for the design and analysis of token algorithms Hadrien Hendrikx FedML 24 13 0 30 May 2022
Perseus: A Simple and Optimal High-Order Method for Variational Inequalities Tianyi Lin Michael I. Jordan 25 10 0 06 May 2022
No-Regret Dynamics in the Fenchel Game: A Unified Framework for Algorithmic Convex Optimization Jun-Kun Wang Jacob D. Abernethy Kfir Y. Levy 24 21 0 22 Nov 2021
Stochastic Primal-Dual Deep Unrolling Junqi Tang Subhadip Mukherjee Carola-Bibiane Schönlieb 24 4 0 19 Oct 2021
ANITA: An Optimal Loopless Accelerated Variance-Reduced Gradient Method Zhize Li 43 14 0 21 Mar 2021
Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques Filip Hanzely Boxin Zhao Mladen Kolar FedML 27 52 0 19 Feb 2021
First-Order Methods for Convex Optimization Pavel Dvurechensky Mathias Staudigl Shimrit Shtern ODL 31 25 0 04 Jan 2021
Optimal Algorithms for Convex Nested Stochastic Composite Optimization Zhe Zhang Guanghui Lan 24 28 0 19 Nov 2020
Lower Bounds and Optimal Algorithms for Personalized Federated Learning Filip Hanzely Slavomír Hanzely Samuel Horváth Peter Richtárik FedML 50 186 0 05 Oct 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 34 0 0 26 Aug 2020
PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization Zhize Li Hongyan Bao Xiangliang Zhang Peter Richtárik ODL 31 125 0 25 Aug 2020
Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization Chaobing Song Yong Jiang Yi Ma 53 23 0 18 Jun 2020
Optimal Complexity in Decentralized Training Yucheng Lu Christopher De Sa 38 72 0 15 Jun 2020
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems Filip Hanzely D. Kovalev Peter Richtárik 35 17 0 11 Feb 2020
The Practicality of Stochastic Optimization in Imaging Inverse Problems Junqi Tang K. Egiazarian Mohammad Golbabaee Mike Davies 27 30 0 22 Oct 2019
Stochastic First-order Methods for Convex and Nonconvex Functional Constrained Optimization Digvijay Boob Qi Deng Guanghui Lan 44 93 0 07 Aug 2019
A Data Efficient and Feasible Level Set Method for Stochastic Convex Optimization with Expectation Constraints Qihang Lin Selvaprabu Nadarajah Negar Soheili Tianbao Yang 27 13 0 07 Aug 2019
Asynchronous decentralized accelerated stochastic gradient descent Guanghui Lan Yi Zhou 13 15 0 24 Sep 2018
Stochastic Nested Variance Reduction for Nonconvex Optimization Dongruo Zhou Pan Xu Quanquan Gu 25 146 0 20 Jun 2018
Lower error bounds for the stochastic gradient descent optimization algorithm: Sharp convergence rates for slowly and fast decaying learning rates Arnulf Jentzen Philippe von Wurstemberger 73 31 0 22 Mar 2018
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization Zhize Li Jian Li 39 116 0 13 Feb 2018
Katyusha X: Practical Momentum Method for Stochastic Sum-of-Nonconvex Optimization Zeyuan Allen-Zhu ODL 44 52 0 12 Feb 2018
Communication-Efficient Algorithms for Decentralized and Stochastic Optimization Guanghui Lan Soomin Lee Yi Zhou 40 218 0 14 Jan 2017
Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data Jialei Wang J. Lee M. Mahdavi Mladen Kolar Nathan Srebro 21 50 0 10 Oct 2016
Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite-Sum Structure A. Bietti Julien Mairal 44 36 0 04 Oct 2016
Dimension-Free Iteration Complexity of Finite Sum Optimization Problems Yossi Arjevani Ohad Shamir 16 24 0 30 Jun 2016
Tight Complexity Bounds for Optimizing Composite Objectives Blake E. Woodworth Nathan Srebro 26 185 0 25 May 2016
Fast Stochastic Methods for Nonsmooth Nonconvex Optimization Sashank J. Reddi S. Sra Barnabás Póczós Alex Smola 20 54 0 23 May 2016
Katyusha: The First Direct Acceleration of Stochastic Gradient Methods Zeyuan Allen-Zhu ODL 15 575 0 18 Mar 2016
A Simple Practical Accelerated Method for Finite Sums Aaron Defazio 25 120 0 08 Feb 2016
Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization Yuchen Zhang Xiao Lin 43 261 0 10 Sep 2014