Near-Optimal Hyperfast Second-Order Method for Convex Optimization

DOI10.1007/978-3-030-58657-7_15zbMath1460.90133arXiv2002.09050OpenAlexW3084935096MaRDI QIDQ4965110

Dmitry Kamzolov

Publication date: 25 February 2021

Published in: Mathematical Optimization Theory and Operations Research (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2002.09050

zbMATH Keywords

complexitysecond-order methodtensor methodinexact method

Mathematics Subject Classification ID

Convex programming (90C25)

Related Items (4)

Local convergence of tensor methods ⋮ Hyperfast second-order local solvers for efficient statistically preconditioned distributed optimization ⋮ Super-Universal Regularized Newton Method ⋮ A control-theoretic perspective on optimal high-order optimization

Cites Work

• Worst-case evaluation complexity for unconstrained nonlinear optimization using high-order regularized models
• Lectures on convex optimization
• Lower bounds for finding stationary points I
• Cubic regularization of Newton method and its global performance
• An Accelerated Hybrid Proximal Extragradient Method for Convex Optimization and Its Implications to Second-Order Methods
• Accelerated Regularized Newton Methods for Minimizing Composite Convex Functions
• Tensor Methods for Minimizing Convex Functions with Hölder Continuous Higher-Order Derivatives
• Contracting Proximal Methods for Smooth Convex Optimization

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