DCA-based algorithms for DC Fitting - Université de Lorraine Accéder directement au contenu
Article Dans Une Revue Journal of Computational and Applied Mathematics Année : 2021

DCA-based algorithms for DC Fitting

Résumé

We investigate a nonconvex, nonsmooth optimization approach based on DC (Difference of Convex functions) programming and DCA (DC Algorithm) for the so-called DC fitting problem, which aims to fit a given set of data points by a DC function. The problem is tackled as minimizing the squared Euclidean norm fitting error. It is formulated as a DC program for which a standard DCA scheme is developed. Furthermore, a modified DCA scheme with successive DC decomposition is proposed. These standard/modified versions of DCA are applied for solving the continuous piecewise-linear fitting problem. Numerical experiments on many synthetic and real datasets with small-to-large sizes show the efficiency of our DCA-based approach in comparison with the existing approaches for constructing continuous piecewise-linear models.
Fichier principal
Vignette du fichier
S0377042720306440.pdf (314.43 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03063899 , version 1 (03-02-2023)

Licence

Paternité - Pas d'utilisation commerciale

Identifiants

Citer

Vinh Thanh Ho, Hoai An Le Thi, Tao Pham Dinh. DCA-based algorithms for DC Fitting. Journal of Computational and Applied Mathematics, 2021, 389, pp.113353. ⟨10.1016/j.cam.2020.113353⟩. ⟨hal-03063899⟩
54 Consultations
5 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More