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» Intractability and clustering with constraints
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ICTAI
2008
IEEE
14 years 6 days ago
Knee Point Detection on Bayesian Information Criterion
The main challenge of cluster analysis is that the number of clusters or the number of model parameters is seldom known, and it must therefore be determined before clustering. Bay...
Qinpei Zhao, Mantao Xu, Pasi Fränti
ICPR
2008
IEEE
14 years 6 days ago
Unsupervised clustering using hyperclique pattern constraints
A novel unsupervised clustering algorithm called Hyperclique Pattern-KMEANS (HP-KMEANS) is presented. Considering recent success in semisupervised clustering using pair-wise const...
Yuchou Chang, Dah-Jye Lee, James K. Archibald, Yi ...
CP
2006
Springer
13 years 9 months ago
The ROOTS Constraint
A wide range of counting and occurrence constraints can be specified with just two global primitives: the Range constraint, which computes the range of values used by a sequence of...
Christian Bessière, Emmanuel Hebrard, Brahi...
DDECS
2008
IEEE
137views Hardware» more  DDECS 2008»
14 years 7 days ago
Cluster-based Simulated Annealing for Mapping Cores onto 2D Mesh Networks on Chip
Abstract—In Network-on-Chip (NoC) application design, coreto-node mapping is an important but intractable optimization problem. In the paper, we use simulated annealing to tackle...
Zhonghai Lu, Lei Xia, Axel Jantsch
EDM
2010
129views Data Mining» more  EDM 2010»
13 years 7 months ago
Skill Set Profile Clustering: The Empty K-Means Algorithm with Automatic Specification of Starting Cluster Centers
While students' skill set profiles can be estimated with formal cognitive diagnosis models [8], their computational complexity makes simpler proxy skill estimates attractive [...
Rebecca Nugent, Nema Dean, Elizabeth Ayers