Zobrazeno 1 - 10
of 6 197
pro vyhledávání: '"SPARSE approximations"'
In this paper we present an efficient active-set method for the solution of convex quadratic programming problems with general piecewise-linear terms in the objective, with applications to sparse approximations and risk-minimization. The algorithm is
Externí odkaz:
http://arxiv.org/abs/2405.04172
Autor:
Kollepara, Kiran Sagar, Aguado, José V., Guennec, Yves Le, Silva, Luisa, Borzacchiello, Domenico
Low-rank model order reduction strategies for contact mechanics show limited dimensionality reduction due to linear inseparability of contact pressure field. Therefore, a dictionary based strategy is explored for creating efficient models for frictio
Externí odkaz:
http://arxiv.org/abs/2406.11461
Autor:
Kollepara, Kiran Sagar
(Rephrased) Non-conformance decision-making processes in high-precision manufacturing of engineering structures are often delayed due to numerical simulations that are needed for analyzing the defective parts and assemblies. Interfaces between parts
Externí odkaz:
http://arxiv.org/abs/2405.20211
Autor:
Mercurio, Paula, Liu, Di
In this paper, we propose an efficient numerical implementation of Network Embedding based on commute times, using sparse approximation of a diffusion process on the network obtained by a modified version of the diffusion wavelet algorithm. The node
Externí odkaz:
http://arxiv.org/abs/2308.13663
Autor:
Levie, Ron1 (AUTHOR), Sochen, Nir2 (AUTHOR)
Publikováno v:
Numerical Functional Analysis & Optimization. 2022, Vol. 43 Issue 11, p1303-1400. 98p.
In this paper we present an efficient active-set method for the solution of convex quadratic programming problems with general piecewise-linear terms in the objective, with applications to sparse approximations and risk-minimization. The method explo
Externí odkaz:
http://arxiv.org/abs/2302.14497
Autor:
Xie, Weixiang1 (AUTHOR) 20212028@sgu.edu.cn, Song, Jie1 (AUTHOR) jiesong@sgu.edu.cn
Publikováno v:
Mathematics (2227-7390). Oct2024, Vol. 12 Issue 19, p2991. 15p.
Autor:
De Simone, Valentina1, di Serafino, Daniela2 daniela.diserafino@unina.it, Gondzio, Jacek3 J.Gondzio@ed.ac.uk, Pougkakiotis, Spyridon3,4 spyridon.pougkakiotis@yale.edu, Viola, Marco1
Publikováno v:
SIAM Review. 2022, Vol. 64 Issue 4, p954-988. 35p.
In this paper we present an active-set method for the solution of $\ell_1$-regularized convex quadratic optimization problems. It is derived by combining a proximal method of multipliers (PMM) strategy with a standard semismooth Newton method (SSN).
Externí odkaz:
http://arxiv.org/abs/2201.10211
Autor:
Bauer, Jan O.1,2 (AUTHOR) janobaue@gmail.com
Publikováno v:
Journal of Computational & Graphical Statistics. Nov2024, p1-19. 19p. 6 Illustrations.