Variance reduction on general adaptive stochastic mirror descent

DOI10.1007/s10994-022-06227-3arXiv2012.13760OpenAlexW4292641443MaRDI QIDQ6097133

Wen-Jie Li, Yi-Chen Zhang, Guang Cheng, Zhanyu Wang

Publication date: 12 June 2023

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2012.13760

zbMATH Keywords

convergence analysisvariance reductionnonconvex nonsmooth optimizationgeneral frameworkadaptive mirror descent

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

An aggressive reduction on the complexity of optimization for non-strongly convex objectives

Cites Work

• The robustness of the \(p\)-norm algorithms
• On the Adaptivity of Stochastic Gradient-Based Optimization
• Mini-batch stochastic approximation methods for nonconvex stochastic composite optimization
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