Non-Asymptotic Convergence Analysis of Inexact Gradient Methods for Machine Learning Without Strong Convexity

31 August 2013

Papers citing "Non-Asymptotic Convergence Analysis of Inexact Gradient Methods for Machine Learning Without Strong Convexity"

6 / 6 papers shown

Title
Federated Optimization of Smooth Loss Functions Ali Jadbabaie A. Makur Devavrat Shah FedML 32 7 0 06 Jan 2022
Gradient-Based Empirical Risk Minimization using Local Polynomial Regression Ali Jadbabaie A. Makur Devavrat Shah 33 6 0 04 Nov 2020
Adaptive Accelerated Gradient Converging Methods under Holderian Error Bound Condition Mingrui Liu Tianbao Yang 37 15 0 23 Nov 2016
A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates Tianbao Yang Qihang Lin Lijun Zhang 19 25 0 11 Aug 2016
RSG: Beating Subgradient Method without Smoothness and Strong Convexity Tianbao Yang Qihang Lin 32 84 0 09 Dec 2015
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 93 737 0 19 Mar 2014