Výsledky vyhledávání - "BELLAVIA, S."

Report

An optimally fast objective-function-free minimization algorithm using random subspaces

Autor: Bellavia, S., Gratton, S., Morini, B., Toint, Ph. L.

An algorithm for unconstrained non-convex optimization is described, which does not evaluate the objective function and in which minimization is carried out, at each iteration, within a randomly selected subspace. It is shown that this random approxi

Externí odkaz: http://arxiv.org/abs/2310.16580

Zobrazit plný text záznamu

Report

Trust-region algorithms: probabilistic complexity and intrinsic noise with applications to subsampling techniques

Autor: Bellavia, S., Gurioli, G., Morini, B., Toint, Ph. L.

A trust-region algorithm is presented for finding approximate minimizers of smooth unconstrained functions whose values and derivatives are subject to random noise. It is shown that, under suitable probabilistic assumptions, the new method finds (in

Externí odkaz: http://arxiv.org/abs/2112.06176

Zobrazit plný text záznamu

Report

Adaptive Regularization for Nonconvex Optimization Using Inexact Function Values and Randomly Perturbed Derivatives

Autor: Bellavia, S., Gurioli, G., Morini, B., Toint, Ph. L.

A regularization algorithm allowing random noise in derivatives and inexact function values is proposed for computing approximate local critical points of any order for smooth unconstrained optimization problems. For an objective function with Lipsch

Externí odkaz: http://arxiv.org/abs/2005.04639

Zobrazit plný text záznamu

Report

Adaptive Regularization Algorithms with Inexact Evaluations for Nonconvex Optimization

Autor: Bellavia, S., Gurioli, G., Morini, B., Toint, Ph. L.

A regularization algorithm using inexact function values and inexact derivatives is proposed and its evaluation complexity analyzed. This algorithm is applicable to unconstrained problems and to problems with inexpensive constraints (that is constrai

Externí odkaz: http://arxiv.org/abs/1811.03831

Zobrazit plný text záznamu

Akademický článek

Trust-region algorithms: Probabilistic complexity and intrinsic noise with applications to subsampling techniques

Autor: Bellavia, S., Gurioli, G., Morini, B., Toint, Ph.L.

Publikováno v: In EURO Journal on Computational Optimization 2022 10

Zobrazit plný text záznamu

Report

Updating constraint preconditioners for KKT systems in quadratic programming via low-rank corrections

Autor: Bellavia, S., De Simone, V., di Serafino, D., Morini, B.

This work focuses on the iterative solution of sequences of KKT linear systems arising in interior point methods applied to large convex quadratic programming problems. This task is the computational core of the interior point procedure and an effici

Externí odkaz: http://arxiv.org/abs/1312.0047

Zobrazit plný text záznamu