Optimal Black-Box Reductions Between Optimization Objectives

17 March 2016

Papers citing "Optimal Black-Box Reductions Between Optimization Objectives"

19 / 19 papers shown

Title
SAPPHIRE: Preconditioned Stochastic Variance Reduction for Faster Large-Scale Statistical Learning Jingruo Sun Zachary Frangella Madeleine Udell 36 0 0 28 Jan 2025
Obtaining Lower Query Complexities through Lightweight Zeroth-Order Proximal Gradient Algorithms Bin Gu Xiyuan Wei Hualin Zhang Yi Chang Heng-Chiao Huang FedML 23 0 0 03 Oct 2024
Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization Liang Zhang Junchi Yang Amin Karbasi Niao He 34 2 0 26 Oct 2023
Impact of Redundancy on Resilience in Distributed Optimization and Learning Shuo Liu Nirupam Gupta Nitin H. Vaidya 34 2 0 16 Nov 2022
Robust Regression Revisited: Acceleration and Improved Estimation Rates A. Jambulapati Jingkai Li T. Schramm Kevin Tian AAML 32 17 0 22 Jun 2021
Asynchronous Distributed Optimization with Redundancy in Cost Functions Shuo Liu Nirupam Gupta Nitin H. Vaidya 26 3 0 07 Jun 2021
First-Order Methods for Convex Optimization Pavel Dvurechensky Mathias Staudigl Shimrit Shtern ODL 31 25 0 04 Jan 2021
Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization Chaobing Song Yong Jiang Yi Ma 53 23 0 18 Jun 2020
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates Kaiwen Zhou Fanhua Shang James Cheng 14 74 0 28 Jun 2018
Katyusha X: Practical Momentum Method for Stochastic Sum-of-Nonconvex Optimization Zeyuan Allen-Zhu ODL 44 52 0 12 Feb 2018
Optimization Methods for Large-Scale Machine Learning Léon Bottou Frank E. Curtis J. Nocedal 90 3,176 0 15 Jun 2016
Tight Complexity Bounds for Optimizing Composite Objectives Blake E. Woodworth Nathan Srebro 36 185 0 25 May 2016
Katyusha: The First Direct Acceleration of Stochastic Gradient Methods Zeyuan Allen-Zhu ODL 15 577 0 18 Mar 2016
Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling Zeyuan Allen-Zhu Zheng Qu Peter Richtárik Yang Yuan 44 172 0 30 Dec 2015
An optimal randomized incremental gradient method Guanghui Lan Yi Zhou 34 220 0 08 Jul 2015
Improved SVRG for Non-Strongly-Convex or Sum-of-Non-Convex Objectives Zeyuan Allen-Zhu Yang Yuan 29 195 0 05 Jun 2015
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 93 737 0 19 Mar 2014
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning Julien Mairal 79 317 0 18 Feb 2014
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method Simon Lacoste-Julien Mark W. Schmidt Francis R. Bach 128 259 0 10 Dec 2012