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KDD
2006
ACM
163views Data Mining» more  KDD 2006»
16 years 7 months ago
New EM derived from Kullback-Leibler divergence
We introduce a new EM framework in which it is possible not only to optimize the model parameters but also the number of model components. A key feature of our approach is that we...
Longin Jan Latecki, Marc Sobel, Rolf Lakämper
KDD
2004
ACM
207views Data Mining» more  KDD 2004»
16 years 7 months ago
Belief state approaches to signaling alarms in surveillance systems
Surveillance systems have long been used to monitor industrial processes and are becoming increasingly popular in public health and anti-terrorism applications. Most early detecti...
Kaustav Das, Andrew W. Moore, Jeff G. Schneider
KDD
2004
ACM
187views Data Mining» more  KDD 2004»
16 years 7 months ago
IMMC: incremental maximum margin criterion
Subspace learning approaches have attracted much attention in academia recently. However, the classical batch algorithms no longer satisfy the applications on streaming data or la...
Jun Yan, Benyu Zhang, Shuicheng Yan, Qiang Yang, H...
KDD
2003
ACM
124views Data Mining» more  KDD 2003»
16 years 7 months ago
Information-theoretic co-clustering
Two-dimensional contingency or co-occurrence tables arise frequently in important applications such as text, web-log and market-basket data analysis. A basic problem in contingenc...
Inderjit S. Dhillon, Subramanyam Mallela, Dharmend...
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