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» A divide-and-merge methodology for clustering
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KDD
2004
ACM
158views Data Mining» more  KDD 2004»
15 years 10 months ago
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...
KDD
2003
ACM
133views Data Mining» more  KDD 2003»
15 years 10 months ago
Interactive Analysis of Gene Interactions Using Graphical gaussian model
DNA microarray provides a powerful basis for analysis of gene expression. Data mining methods such as clustering have been widely applied to microarray data to link genes that sho...
Xintao Wu, Yong Ye, Kalpathi R. Subramanian
SAC
2009
ACM
15 years 4 months ago
A new protein motif extraction framework based on constrained co-clustering
Signal finding (pattern discovery) in biological sequences is a fundamental problem in both computer science and molecular biology. Many approaches have been proposed for extract...
Francesca Cordero, Alessia Visconti, Marco Botta
CCGRID
2007
IEEE
15 years 4 months ago
Adaptive Performance Modeling on Hierarchical Grid Computing Environments
In the past, efficient parallel algorithms have always been developed specifically for the successive generations of parallel systems (vector machines, shared-memory machines, d...
Wahid Nasri, Luiz Angelo Steffenel, Denis Trystram
GECCO
2007
Springer
289views Optimization» more  GECCO 2007»
15 years 4 months ago
A discrete particle swarm optimization algorithm for the generalized traveling salesman problem
Dividing the set of nodes into clusters in the well-known traveling salesman problem results in the generalized traveling salesman problem which seeking a tour with minimum cost p...
Mehmet Fatih Tasgetiren, Ponnuthurai N. Suganthan,...