Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Spyridon Pougkakiotis"'
Publikováno v:
Computational Optimization and Applications. 83:727-757
In this paper we present general-purpose preconditioners for regularized augmented systems, and their corresponding normal equations, arising from optimization problems. We discuss positive definite preconditioners, suitable for CG and MINRES. We con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::16132ea6e033a210b510ce20b690d011
https://doi.org/10.1007/s10589-022-00424-5
https://doi.org/10.1007/s10589-022-00424-5
Autor:
Spyridon Pougkakiotis, Jacek Gondzio
Publikováno v:
Journal of Optimization Theory and Applications. 192:97-129
In this paper we generalize the Interior Point-Proximal Method of Multipliers (IP-PMM) presented in Pougkakiotis and Gondzio (Comput Optim Appl 78:307–351, 2021.10.1007/s10589-020-00240-9) for the solution of linear positive Semi-Definite Programmi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::19693665e1fd93ac67bf09afff58535e
https://doi.org/10.1007/s10957-021-01954-4
https://doi.org/10.1007/s10957-021-01954-4
Publikováno v:
Pougkakiotis, S, Pearson, J W, Leveque, S & Gondzio, J 2020, ' FAST SOLUTION METHODS FOR CONVEX QUADRATIC OPTIMIZATION OF FRACTIONAL DIFFERENTIAL EQUATIONS ', SIAM Journal on Matrix Analysis and Applications, vol. 41, no. 3, pp. 1443–1476 . https://doi.org/10.1137/19M128288X
In this paper, we present numerical methods suitable for solving convex quadratic Fractional Differential Equation (FDE) constrained optimization problems, with box constraints on the state and/or control variables. We develop an Alternating Directio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d58e9696584f9061fbb0ca25c4b1833f
https://doi.org/10.1137/19m128288x
https://doi.org/10.1137/19m128288x
Large-scale optimization problems that seek sparse solutions have become ubiquitous. They are routinely solved with various specialized first-order methods. Although such methods are often fast, they usually struggle with not-so-well conditioned prob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5863337afea787fa118bb166a76e7ac
Autor:
Spyridon Pougkakiotis, Jacek Gondzio
Publikováno v:
Pougkakiotis, S & Gondzio, J 2019, ' Dynamic Non-Diagonal Regularization in Interior Point Methods for Linear and Convex Quadratic Programming ', Journal of Optimization Theory and Applications, vol. 181, no. 3, pp. 905-945 . https://doi.org/10.1007/s10957-019-01491-1
In this paper, we present a dynamic non-diagonal regularization for interior point methods. The non-diagonal aspect of this regularization is implicit, since all the off-diagonal elements of the regularization matrices are cancelled out by those elem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0205aa19563f3c2f9943bedd1f5e5243
https://hdl.handle.net/20.500.11820/03623f03-7938-4e00-8d16-b25b3b247bc6
https://hdl.handle.net/20.500.11820/03623f03-7938-4e00-8d16-b25b3b247bc6
Publikováno v:
Bergamaschi, L, Gondzio, J, Martínez, Á, Pearson, J W & Pougkakiotis, S 2021, ' A New Preconditioning Approachfor an Interior Point–Proximal Method of Multipliers for Linear and Convex Quadratic Programming ', Numerical Linear Algebra with Applications . https://doi.org/10.1002/nla.2361
In this article, we address the efficient numerical solution of linear and quadratic programming problems, often of large scale. With this aim, we devise an infeasible interior point method, blended with the proximal method of multipliers, which in t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c6fd284fcfdff1b0c2bf50fb0cc9fcb4
Publikováno v:
SSP
We present a new framework for online Least Squares algorithms for nonlinear modeling in RKH spaces (RKHS). Instead of implicitly mapping the data to a RKHS (e.g., kernel trick), we map the data to a finite dimensional Euclidean space, using random f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cd959c7b6abc4f5379428f70ddb134ca
http://arxiv.org/abs/1606.03685
http://arxiv.org/abs/1606.03685