H.A. Le Thi, Collaborative DCA: an intelligent collective optimization scheme, and its application for clustering.

Abstract: This paper deals with a new and efficient collective optimization approach, based on DC (Difference of Convex functions) programming and DCA (DC Algorithm), powerful tools of nonconvex programming. Exploiting the efficiency and the flexibility of DCA we develop the so-called collaborative DCA in which divers DCA based algorithms are cooperated in an effective way. Two versions of collaborative DCA are proposed and their applications on clustering, a fundamental problem in unsupervised learning, are studied. Numerical experiments are performed on several datasets. The comparative results with three DCA component algorithms show that the collaborative DCA outperforms them on quality and it realizes a good trade-off between the quality of solutions and the running time.

 

Keywords: Collective optimization, DC programming, DCA, Collaborative DCA, Clustering.

 

Citation: Hoai An Le Thi, Collaborative DCA: an intelligent collective optimization scheme, and its application for clustering. Journal of Intelligent & Fuzzy Systems, Volume 37, Issue 6, pp. 7511-7518, December 2019.

 

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