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» The Method of Quantum Clustering
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ICDM
2009
IEEE
132views Data Mining» more  ICDM 2009»
16 years 1 months ago
Bayesian Overlapping Subspace Clustering
Given a data matrix, the problem of finding dense/uniform sub-blocks in the matrix is becoming important in several applications. The problem is inherently combinatorial since th...
Qiang Fu, Arindam Banerjee
ICDM
2009
IEEE
117views Data Mining» more  ICDM 2009»
16 years 1 months ago
Clustering with Multiple Graphs
—In graph-based learning models, entities are often represented as vertices in an undirected graph with weighted edges describing the relationships between entities. In many real...
Wei Tang, Zhengdong Lu, Inderjit S. Dhillon
ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
16 years 1 months ago
Semi-supervised Clustering Using Bayesian Regularization
Text clustering is most commonly treated as a fully automated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwi...
Zuobing Xu, Ram Akella, Mike Ching, Renjie Tang
ISI
2007
Springer
16 years 28 days ago
DOTS: Detection of Off-Topic Search via Result Clustering
— Often document dissemination is limited to a “need to know” basis so as to better maintain organizational trade secrets. Retrieving documents that are off-topic to a user...
Nazli Goharian, Alana Platt
PAKDD
2007
ACM
152views Data Mining» more  PAKDD 2007»
16 years 27 days ago
Spectral Clustering Based Null Space Linear Discriminant Analysis (SNLDA)
While null space based linear discriminant analysis (NLDA) obtains a good discriminant performance, the ability easily suffers from an implicit assumption of Gaussian model with sa...
Wenxin Yang, Junping Zhang