Solving the Euclidean k-median problem by DCA

被引：0
|
作者：
Le Thi Hoai An [1 ]
Pham Dinh Tao [2 ]
机构：
[1] Paul Verlaine Metz Univ, Lab Theoret & Appl Comp Sci LITA, F-57045 Metz, France
[2] Natl Inst Appl Sci, Lab Modelling Optimizat & Operat, St Etienne Du Rouvray, France
来源：
SELECTED TOPICS IN APPLIED COMPUTER SCIENCE | 2010年
关键词：
nonconvexe optimization; nonsmooth optimization; DC programming; DCA; K-median-clustering; OPTIMIZATION; ALGORITHM;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this paper, a novel optimization model for k-median clustering has been proposed. This is a hard nonconvex, nonsmooth optimization problem for which we investigate an efficient technique based on DC (Difference of Convex functions) programming and DCA (DC Algorithm). Preliminary numerical results on some real-world databases show the efficiency of the proposed approach
引用
收藏
页码：394 / +
页数：3
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