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» Approximation Algorithms for Clustering Problems
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CEC
2009
IEEE
16 years 24 days ago
A clustering multi-objective evolutionary algorithm based on orthogonal and uniform design
Abstract— Designing efficient algorithms for difficult multiobjective optimization problems is a very challenging problem. In this paper a new clustering multi-objective evolut...
Yuping Wang, Chuangyin Dang, Hecheng Li, Lixia Han...
SIGIR
2006
ACM
15 years 12 months ago
Feature diversity in cluster ensembles for robust document clustering
The performance of document clustering systems depends on employing optimal text representations, which are not only difficult to determine beforehand, but also may vary from one ...
Xavier Sevillano, Germán Cobo, Francesc Al&...
WADS
2009
Springer
274views Algorithms» more  WADS 2009»
16 years 19 days ago
Approximating Transitive Reductions for Directed Networks
Abstract. We consider minimum equivalent digraph problem, its maximum optimization variant and some non-trivial extensions of these two types of problems motivated by biological an...
Piotr Berman, Bhaskar DasGupta, Marek Karpinski
SDM
2009
SIAM
176views Data Mining» more  SDM 2009»
16 years 3 months ago
Constraint-Based Subspace Clustering.
In high dimensional data, the general performance of traditional clustering algorithms decreases. This is partly because the similarity criterion used by these algorithms becomes ...
Élisa Fromont, Adriana Prado, Céline...
GECCO
2004
Springer
124views Optimization» more  GECCO 2004»
15 years 11 months ago
Clustering with Niching Genetic K-means Algorithm
GA-based clustering algorithms often employ either simple GA, steady state GA or their variants and fail to consistently and efficiently identify high quality solutions (best known...
Weiguo Sheng, Allan Tucker, Xiaohui Liu