Adaptive regularization for nonconvex optimization using inexact function values and randomly perturbed derivatives
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Publication:2052165
DOI10.1016/j.jco.2021.101591zbMath1481.90287arXiv2005.04639OpenAlexW3184878065MaRDI QIDQ2052165
Publication date: 25 November 2021
Published in: Journal of Complexity (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2005.04639
Related Items (6)
Inexact restoration for minimization with inexact evaluation both of the objective function and the constraints ⋮ Convergence Properties of an Objective-Function-Free Optimization Regularization Algorithm, Including an \(\boldsymbol{\mathcal{O}(\epsilon^{-3/2})}\) Complexity Bound ⋮ Trust-region algorithms: probabilistic complexity and intrinsic noise with applications to subsampling techniques ⋮ The impact of noise on evaluation complexity: the deterministic trust-region case ⋮ Linesearch Newton-CG methods for convex optimization with noise ⋮ A stochastic first-order trust-region method with inexact restoration for finite-sum minimization
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