Fast and safe: accelerated gradient methods with optimality certificates and underestimate sequences

DOI10.1007/s10589-021-00269-4zbMath1473.90115arXiv1710.03695OpenAlexW3154674907MaRDI QIDQ2044479

Majid Jahani, Chenxin Ma, Martin Takáč, Rachael Tappenden, Naga Venkata C. Gudapati

Publication date: 9 August 2021

Published in: Computational Optimization and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1710.03695

zbMATH Keywords

lower boundsstrongly convexcomposite minimizationsmooth minimizationaccelerated algorithmsestimate sequencequadratic averagingunderestimate sequence

Mathematics Subject Classification ID

Analysis of algorithms and problem complexity (68Q25) Convex programming (90C25) Minimax problems in mathematical programming (90C47)

Related Items (1)

New analysis of linear convergence of gradient-type methods via unifying error bound conditions

Uses Software

• LIBSVM
• Adam

Cites Work

• Unnamed Item
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