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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A fast gradient and function sampling method for finite-max functions

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Author(s):
Helou, Elias S. [1] ; Santos, Sandra A. [2] ; Simoes, Lucas E. A. [2]
Total Authors: 3
Affiliation:
[1] Univ Sao Paulo, Inst Math Sci & Computat, Sao Carlos, SP - Brazil
[2] Univ Estadual Campinas, Dept Appl Math, Campinas, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: COMPUTATIONAL OPTIMIZATION AND APPLICATIONS; v. 71, n. 3, p. 673-717, DEC 2018.
Web of Science Citations: 0
Abstract

This paper proposes an algorithm for the unconstrained minimization of a class of nonsmooth and nonconvex functions that can be written as finite-max functions. A gradient and function-based sampling method is proposed which, under special circumstances, either moves superlinearly to a minimizer of the problem of interest or improves the optimality certificate. Global and local convergence analysis are presented, as well as examples that illustrate the obtained theoretical results. (AU)

FAPESP's process: 13/05475-7 - Computational methods in optimization
Grantee:Sandra Augusta Santos
Support type: Research Projects - Thematic Grants
FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:José Alberto Cuminato
Support type: Research Grants - Research, Innovation and Dissemination Centers - RIDC
FAPESP's process: 16/22989-2 - A sampling method for constrained nonsmooth optimization problems
Grantee:Lucas Eduardo Azevedo Simões
Support type: Scholarships in Brazil - Post-Doctorate
FAPESP's process: 13/16508-3 - Fast computation of the generalized Backprojection operator with applications in tomographic image reconstruction
Grantee:Elias Salomão Helou Neto
Support type: Regular Research Grants
FAPESP's process: 13/14615-7 - On the nonmonotone line search in gradient sampling methods for nonconvex and nonsmooth optimization
Grantee:Lucas Eduardo Azevedo Simões
Support type: Scholarships in Brazil - Doctorate