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» Clustering with Bregman Divergences
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KDD
2005
ACM
112views Data Mining» more  KDD 2005»
14 years 4 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,...
CORR
2006
Springer
154views Education» more  CORR 2006»
13 years 3 months ago
Functional Bregman Divergence and Bayesian Estimation of Distributions
Abstract--A class of distortions termed functional Bregman divergences is defined, which includes squared error and relative entropy. A functional Bregman divergence acts on functi...
B. A. Frigyik, Santosh Srivastava, Maya R. Gupta

Publication
1763views
14 years 21 hour ago
Reranking with Contextual dissimilarity measures from representational Bregman k-means
We present a novel reranking framework for Content Based Image Retrieval (CBIR) systems based on con-textual dissimilarity measures. Our work revisit and extend the method of Perro...
Olivier Schwander, Frank Nielsen
CVPR
2010
IEEE
13 years 3 months ago
Total Bregman divergence and its applications to shape retrieval
Shape database search is ubiquitous in the world of biometric systems, CAD systems etc. Shape data in these domains is experiencing an explosive growth and usually requires search...
Meizhu Liu, Baba C. Vemuri, Shun-ichi Amari, Frank...
SDM
2004
SIAM
189views Data Mining» more  SDM 2004»
13 years 5 months ago
An Abstract Weighting Framework for Clustering Algorithms
act Weighting Framework for Clustering Algorithms Richard Nock Frank Nielsen Recent works in unsupervised learning have emphasized the need to understand a new trend in algorithmi...
Richard Nock, Frank Nielsen