Zobrazeno 1 - 10
of 138
pro vyhledávání: '"Nicholas I. M. Gould"'
Publikováno v:
Optimization Methods and Software. 35:243-256
An adaptive regularization algorithm is proposed that uses Taylor models of the objective of order p, (Formula presented.), of the unconstrained objective function, and that is guaranteed to find a first- and second-order critical point in at most (F
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e19ac682fc9746c0364b889009f43696
https://doi.org/10.1080/10556788.2019.1678033
https://doi.org/10.1080/10556788.2019.1678033
Publikováno v:
Optimization methods & software
35 (2019): 304–328. doi:10.1080/10556788.2019.1670177
info:cnr-pdr/source/autori:N.I. Gould and V. Simoncini/titolo:Error estimates for iterative algorithms for minimizing regularized quadratic subproblems/doi:10.1080%2F10556788.2019.1670177/rivista:Optimization methods & software (Print)/anno:2019/pagina_da:304/pagina_a:328/intervallo_pagine:304–328/volume:35
35 (2019): 304–328. doi:10.1080/10556788.2019.1670177
info:cnr-pdr/source/autori:N.I. Gould and V. Simoncini/titolo:Error estimates for iterative algorithms for minimizing regularized quadratic subproblems/doi:10.1080%2F10556788.2019.1670177/rivista:Optimization methods & software (Print)/anno:2019/pagina_da:304/pagina_a:328/intervallo_pagine:304–328/volume:35
We derive bounds for the objective errors and gradient residuals when finding approximations to the solution of common regularized quadratic optimization problems within evolving Krylov spaces. These provide upper bounds on the number of iterations r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dfb9c1c6208e420f49b607f7ff2d3a17
https://doi.org/10.1080/10556788.2019.1670177
https://doi.org/10.1080/10556788.2019.1670177
Publikováno v:
Computational Optimization and Applications. 73:1-35
Given a twice-continuously differentiable vector-valued function r(x), a local minimizer of $$\Vert r(x)\Vert _2$$ is sought. We propose and analyse tensor-Newton methods, in which r(x) is replaced locally by its second-order Taylor approximation. Co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a80e6707236fc7846b3b9b4c7b2c46c9
https://doi.org/10.1007/s10589-019-00064-2
https://doi.org/10.1007/s10589-019-00064-2
Publikováno v:
Toint, P 2017, ' Worst-case evaluation complexity of regularization methods for smooth unconstrained optimization using Hölder continuous gradients ', Optimization Methods and Software, vol. 32, no. 6, pp. 1273-1298 . https://doi.org/10.1080/10556788.2016.1268136
The worst-case behaviour of a general class of regularization algorithms is considered in the case where only objective function values and associated gradient vectors are evaluated. Upper bounds are derived on the number of such evaluations that are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a75119731d43a1ec8734ef1a4435852a
https://researchportal.unamur.be/en/publications/bc81bf28-15b6-4fa0-b632-a6fee775d459
https://researchportal.unamur.be/en/publications/bc81bf28-15b6-4fa0-b632-a6fee775d459
Publikováno v:
ACM Transactions on Mathematical Software. 43:1-35
In recent years, a variety of preconditioners have been proposed for use in solving large sparse linear least-squares problems. These include simple diagonal preconditioning, preconditioners based on incomplete factorizations, and stationary inner it
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::24f93e5d9bec19c5076f91a972ef989b
https://doi.org/10.1145/3014057
https://doi.org/10.1145/3014057
Publikováno v:
Cartis, C, Fowkes, J M & Gould, N I M 2015, ' Branching and bounding improvements for global optimization algorithms with Lipschitz continuity properties ', Journal of Global Optimization, vol. 61, no. 3, pp. 429-457 . https://doi.org/10.1007/s10898-014-0199-6
Cartis, C, Fowkes, J & Gould, N 2013, Branching and Bounding Improvements for Global Optimization Algorithms with Lipschitz Continuity Properties . vol. 13-010 .
Cartis, C, Fowkes, J & Gould, N 2013, Branching and Bounding Improvements for Global Optimization Algorithms with Lipschitz Continuity Properties . vol. 13-010 .
We present improvements to branch and bound techniques for globally optimizing functions with Lipschitz continuity properties by developing novel bounding procedures and parallelisation strategies. The bounding procedures involve nonconvex quadratic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f43468199cfae376bcecde0afda50f8
https://ora.ox.ac.uk/objects/uuid:7806d930-6121-4676-b896-a873c18a0b04
https://ora.ox.ac.uk/objects/uuid:7806d930-6121-4676-b896-a873c18a0b04
In a recent paper (Cartis et al. in Math Prog A 144(2):93---106, 2014), the evaluation complexity of an algorithm to find an approximate first-order critical point for the general smooth constrained optimization problem was examined. Unfortunately, t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a94dd04c72f728cb3b4e90d2f171d3b8
https://doi.org/10.1007/s10107-016-1016-4
https://doi.org/10.1007/s10107-016-1016-4
Publikováno v:
Approximation and Optimization ISBN: 9783030127664
Evaluation complexity for convexly constrained optimization is considered and it is shown first that the complexity bound of O(𝜖−3∕2) proved by Cartis et al. (IMA J Numer Anal 32:1662–1695, 2012) for computing an 𝜖-approximate first-order
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::533cfae8cb1b8979c9e143c890b7f4ea
https://doi.org/10.1007/978-3-030-12767-1_2
https://doi.org/10.1007/978-3-030-12767-1_2
Autor:
Stefan Vigerske, Pietro Belotti, Nikolaos V. Sahinidis, Nicholas I. M. Gould, Emiliano Traversi, Ambros M. Gleixner, Ruth Misener, Fabio Furini, Andrea Lodi, Hans D. Mittelmann, Angelika Wiegele, Antonio Frangioni, Leo Liberti
Publikováno v:
Mathematical programming computation (Internet) 11 (2019): 237–265. doi:10.1007/s12532-018-0147-4
info:cnr-pdr/source/autori:Furini F.; Traversi E.; Belotti P.; Frangioni A.; Gleixner A.; Gould N.; Liberti L.; Lodi A.; Misener R.; Mittelmann H.; Sahinidis N.V.; Vigerske S.; Wiegele A./titolo:QPLIB: a library of quadratic programming instances/doi:10.1007%2Fs12532-018-0147-4/rivista:Mathematical programming computation (Internet)/anno:2019/pagina_da:237/pagina_a:265/intervallo_pagine:237–265/volume:11
Mathematical programming computation
(2018). doi:10.5281/zenodo.1412045
info:cnr-pdr/source/autori:Fabio Furini, Emiliano Traversi, Pietro Belotti, Antonio Frangioni, Ambros Gleixner, Nick Gould, Leo Liberti,Andrea Lodi, Ruth Misener, Hans Mittelmann, Nikolaos V. Sahinidis, Stefan Vigerske, Angelika Wiegele/titolo:QPLIB: A Library of Quadratic Programming Instances/doi:10.5281%2Fzenodo.1412045/rivista:Mathematical programming computation (Print)/anno:2018/pagina_da:/pagina_a:/intervallo_pagine:/volume
Mathematical Programming Computation
Mathematical Programming Computation, 2019, 11 (2), ⟨10.1007/s12532-018-0147-4⟩
info:cnr-pdr/source/autori:Furini F.; Traversi E.; Belotti P.; Frangioni A.; Gleixner A.; Gould N.; Liberti L.; Lodi A.; Misener R.; Mittelmann H.; Sahinidis N.V.; Vigerske S.; Wiegele A./titolo:QPLIB: a library of quadratic programming instances/doi:10.1007%2Fs12532-018-0147-4/rivista:Mathematical programming computation (Internet)/anno:2019/pagina_da:237/pagina_a:265/intervallo_pagine:237–265/volume:11
Mathematical programming computation
(2018). doi:10.5281/zenodo.1412045
info:cnr-pdr/source/autori:Fabio Furini, Emiliano Traversi, Pietro Belotti, Antonio Frangioni, Ambros Gleixner, Nick Gould, Leo Liberti,Andrea Lodi, Ruth Misener, Hans Mittelmann, Nikolaos V. Sahinidis, Stefan Vigerske, Angelika Wiegele/titolo:QPLIB: A Library of Quadratic Programming Instances/doi:10.5281%2Fzenodo.1412045/rivista:Mathematical programming computation (Print)/anno:2018/pagina_da:/pagina_a:/intervallo_pagine:/volume
Mathematical Programming Computation
Mathematical Programming Computation, 2019, 11 (2), ⟨10.1007/s12532-018-0147-4⟩
Le PDF est la pré-publication (version soumise); International audience; This paper describes a new instance library for quadratic programming (QP), i.e., the family of continuous and (mixed)-integer optimization problems where the objective functio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c6a6cc530747f4e5867c3eebc364ba3
http://hdl.handle.net/11568/930999
http://hdl.handle.net/11568/930999