- Title
- Nonsmooth DC programming approach to the minimum sum-of-squares clustering problems
- Creator
- Bagirov, Adil; Taheri, Sona; Ugon, Julien
- Date
- 2016
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/100437
- Identifier
- vital:10544
- Identifier
-
https://doi.org/10.1016/j.patcog.2015.11.011
- Identifier
- ISSN:0031-3203
- Abstract
- This paper introduces an algorithm for solving the minimum sum-of-squares clustering problems using their difference of convex representations. A non-smooth non-convex optimization formulation of the clustering problem is used to design the algorithm. Characterizations of critical points, stationary points in the sense of generalized gradients and inf-stationary points of the clustering problem are given. The proposed algorithm is tested and compared with other clustering algorithms using large real world data sets. © 2015 Elsevier Ltd. All rights reserved.
- Publisher
- Elsevier Ltd
- Relation
- Pattern Recognition Vol. 53, no. (2016), p. 12-24; http://purl.org/au-research/grants/arc/DP140103213
- Rights
- Copyright © 2015 Elsevier Ltd. All rights reserved.
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0899 Other Information and Computing Sciences; 0906 Electrical and Electronic Engineering; 0801 Artificial Intelligence and Image Processing; Cluster analysis; Incremental clustering algorithms; Non-convex optimization; Non-smooth optimization
- Reviewed
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