Gradient methods with memory

DOI10.1080/10556788.2020.1858831zbMath1502.90132arXiv2105.09241OpenAlexW3162537520MaRDI QIDQ5043847

Mihai I. Florea, Yu. E. Nesterov

Publication date: 6 October 2022

Published in: Optimization Methods and Software (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2105.09241

zbMATH Keywords

rate of convergenceconvex optimizationgradient methodsrelative smoothnesspiece-wise linear model

Mathematics Subject Classification ID

Convex programming (90C25) Methods of reduced gradient type (90C52)

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Cites Work

• Gradient methods for minimizing composite functions
• Lectures on convex optimization
• Complexity bounds for primal-dual methods minimizing the model of objective function
• An Optimal First Order Method Based on Optimal Quadratic Averaging
• Relatively Smooth Convex Optimization by First-Order Methods, and Applications
• A Descent Lemma Beyond Lipschitz Gradient Continuity: First-Order Methods Revisited and Applications

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