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» Cost-Sensitive Learning Based on Bregman Divergences
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PKDD
2009
Springer
138views Data Mining» more  PKDD 2009»
9 years 1 months ago
Cost-Sensitive Learning Based on Bregman Divergences
Raúl Santos-Rodríguez, Alicia Guerre...
SDM
2004
SIAM
212views Data Mining» more  SDM 2004»
8 years 10 months ago
Clustering with Bregman Divergences
A wide variety of distortion functions, such as squared Euclidean distance, Mahalanobis distance, Itakura-Saito distance and relative entropy, have been used for clustering. In th...
Arindam Banerjee, Srujana Merugu, Inderjit S. Dhil...
KDD
2004
ACM
158views Data Mining» more  KDD 2004»
9 years 9 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
2005
ACM
112views Data Mining» more  KDD 2005»
9 years 9 months ago
Model-based overlapping clustering
While the vast majority of clustering algorithms are partitional, many real world datasets have inherently overlapping clusters. Several approaches to finding overlapping clusters...
Arindam Banerjee, Chase Krumpelman, Joydeep Ghosh,...
ICASSP
2010
IEEE
8 years 9 months ago
Hierarchical Gaussian Mixture Model
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
Vincent Garcia, Frank Nielsen, Richard Nock
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