A stochastic gradient method with variance control and variable learning rate for deep learning
type: Item
instance of: scholarly article
title: A stochastic gradient method with variance control and variable learning rate for deep learning
author: Giorgia Franchini
author: F. Porta
author: V. Ruggiero
author: Ilaria Trombini
author: Luca Zanni
published in: Journal of Computational and Applied Mathematics
publication date: 2024-08-01T00:00:00Z
Mathematics Subject Classification ID: 90C30
Mathematics Subject Classification ID: 90C15
zbMATH DE Number: 7890914
zbMATH Keywords: stochastic gradient method
zbMATH Keywords: line search
zbMATH Keywords: hyperparameters tuning
zbMATH Keywords: deep learning
MaRDI profile type: Publication
cites work: Optimization Methods for Large-Scale Machine Learning
cites work: A Stochastic Approximation Method
cites work: Hybrid deterministic-stochastic methods for data fitting
cites work: Sample size selection in optimization methods for machine learning
cites work: Adaptive Sampling Strategies for Stochastic Optimization
cites work: A line search based proximal stochastic gradient algorithm with dynamical variance reduction
cites work: A Stochastic Line Search Method with Expected Complexity Analysis
cites work: Q3102800
cites work: Nonmonotone line search methods with variable sample size
cites work: Q5621842
DOI: 10.1016/J.CAM.2024.116083
description: scientific article; zbMATH DE number 7890914