Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Harry Oviedo"'
Autor:
Harry Oviedo
Publikováno v:
Mathematics, Vol 11, Iss 11, p 2414 (2023)
In this paper, we consider the problem of minimizing a continuously differentiable function on the Stiefel manifold. To solve this problem, we develop a geodesic-free proximal point algorithm equipped with Euclidean distance that does not require use
Externí odkaz:
https://doaj.org/article/0d0a9f86bed246babb914595c92625e7
Publikováno v:
Bulletin of Computational Applied Mathematics, Vol 2, Iss 2, Pp 21-46 (2015)
The matrix completion problem (MC) has been approximated by using the nuclear norm relaxation. Some algorithms based on this strategy require the computationally expensive singular value decomposition (SVD) at each iteration. One way to avoid SVD cal
Externí odkaz:
https://doaj.org/article/51d51a82defa4ba18782696211ea66ad
Publikováno v:
Optimization Letters. 17:1069-1081
Generalized circumcenters have been recently introduced and employed to speed up classical projection-type methods for solving feasibility problems. In this note, circumcenters are enforced in a new setting; they are proven to provide inward directio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad2f60e9d9d76978c46483e6e2bd19fa
https://doi.org/10.1007/s11590-022-01923-4
https://doi.org/10.1007/s11590-022-01923-4
Autor:
Harry Oviedo
Publikováno v:
Numerical Algorithms. 91:1183-1203
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7354f2b8bcb3dd9d5c8a8bc869781518
https://doi.org/10.1007/s11075-022-01298-8
https://doi.org/10.1007/s11075-022-01298-8
Publikováno v:
Numerical Algorithms. 90:1225-1252
We introduce a family of weighted conjugate-gradient-type methods, for strictly convex quadratic functions, whose parameters are determined by a minimization model based on a convex combination of the objective function and its gradient norm. This fa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0997fc9806bf9e1c48485ec912df94f4
https://doi.org/10.1007/s11075-021-01228-0
https://doi.org/10.1007/s11075-021-01228-0
Autor:
Harry Oviedo
Publikováno v:
Optimization Letters. 16:1773-1797
Optimization problems with orthogonality constraints appear widely in applications from science and engineering. We address these types of problems from a numerical approach. Our new framework combines the steepest gradient descent, using implicit in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9f16043d898361e6909460a5162e481
https://doi.org/10.1007/s11590-021-01801-5
https://doi.org/10.1007/s11590-021-01801-5
Publikováno v:
BIT Numerical Mathematics. 62:591-606
In this article we address the problem of minimizing a strictly convex quadratic function using a novel iterative method. The new algorithm is based on the well-known Nesterov’s accelerated gradient method. At each iteration of our scheme, the new
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1eb51f0493a15127b4aeaf25d7381e1a
https://doi.org/10.1007/s10543-021-00886-9
https://doi.org/10.1007/s10543-021-00886-9
Autor:
Harry Oviedo
Publikováno v:
Journal of Computational Mathematics. 39:375-391
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ff380ed74fff486c5b93bc253747f4e7
https://doi.org/10.4208/jcm.2001-m2018-0205
https://doi.org/10.4208/jcm.2001-m2018-0205
Publikováno v:
Numerical Algorithms. 87:1107-1127
This article is concerned with the problem of minimizing a smooth function over the Stiefel manifold. In order to address this problem, we introduce two adaptive scaled gradient projection methods that incorporate scaling matrices that depend on the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f6c50c12be065e915f0043885d744ddc
https://doi.org/10.1007/s11075-020-01001-9
https://doi.org/10.1007/s11075-020-01001-9
Autor:
Harry Oviedo
Publikováno v:
Revista Colombiana de Matemáticas, Volume: 55, Issue: 1, Pages: 109-123, Published: 17 NOV 2021
This paper addresses the positive semi-definite procrustes problem (PSDP). The PSDP corresponds to a least squares problem over the set of symmetric and semi-definite positive matrices. These kinds of problems appear in many applications such as stru
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8ed3ccdecd80eb732cfa43b69b3d16ae
http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0034-74262021000100109&lng=en&tlng=en
http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0034-74262021000100109&lng=en&tlng=en
