On the rates of convergence of parallelized averaged stochastic gradient algorithms

DOI10.1080/02331888.2020.1764557zbMath1440.62313arXiv1710.07926OpenAlexW3026202352MaRDI QIDQ5110810

Antoine Godichon-Baggioni, Sofiane Saadane

Publication date: 23 May 2020

Published in: Unnamed Author (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1710.07926

zbMATH Keywords

central limit theoremaveragingstochastic gradient descentdistributed estimationasynchronous parallel optimization

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Central limit and other weak theorems (60F05) Stochastic approximation (62L20)

Related Items (1)

Decentralized and parallel primal and dual accelerated methods for stochastic convex programming problems

Uses Software

• Jellyfish

Cites Work

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• Efficient and fast estimation of the geometric median in Hilbert spaces with an averaged stochastic gradient algorithm
• Estimating the geometric median in Hilbert spaces with stochastic gradient algorithms: \(L^p\) and almost sure rates of convergence
• Stochastic heavy ball
• On the almost sure asymptotic behaviour of stochastic algorithm
• Online estimation of the geometric median in Hilbert spaces: nonasymptotic confidence balls
• Online estimation of the asymptotic variance for averaged stochastic gradient algorithms
• Parallel stochastic gradient algorithms for large-scale matrix completion
• Adaptivity of averaged stochastic gradient descent to local strong convexity for logistic regression
• Acceleration of Stochastic Approximation by Averaging
• Asymptotic Almost Sure Efficiency of Averaged Stochastic Algorithms
• On Projected Stochastic Gradient Descent Algorithm with Weighted Averaging for Least Squares Regression
• Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression
• Optimal Stochastic Approximation Algorithms for Strongly Convex Stochastic Composite Optimization I: A Generic Algorithmic Framework
• Performance of a Distributed Stochastic Approximation Algorithm
• An Asynchronous Parallel Stochastic Coordinate Descent Algorithm
• Note on the median of a multivariate distribution
• A Stochastic Approximation Method
• L^p and almost sure rates of convergence of averaged stochastic gradient algorithms: locally strongly convex objective

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