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» Clustering with Bregman Divergences
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ICASSP
2010
IEEE
13 years 7 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
ICMCS
2009
IEEE
205views Multimedia» more  ICMCS 2009»
13 years 5 months ago
Bregman vantage point trees for efficient nearest Neighbor Queries
Nearest Neighbor (NN) retrieval is a crucial tool of many computer vision tasks. Since the brute-force naive search is too time consuming for most applications, several tailored d...
Frank Nielsen, Paolo Piro, Michel Barlaud
TALG
2010
158views more  TALG 2010»
13 years 2 months ago
Clustering for metric and nonmetric distance measures
We study a generalization of the k-median problem with respect to an arbitrary dissimilarity measure D. Given a finite set P of size n, our goal is to find a set C of size k such t...
Marcel R. Ackermann, Johannes Blömer, Christi...
NIPS
2008
13 years 9 months ago
On the Reliability of Clustering Stability in the Large Sample Regime
Clustering stability is an increasingly popular family of methods for performing model selection in data clustering. The basic idea is that the chosen model should be stable under...
Ohad Shamir, Naftali Tishby
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
14 years 8 months ago
Unsupervised learning on k-partite graphs
Various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. However, the resear...
Bo Long, Xiaoyun Wu, Zhongfei (Mark) Zhang, Philip...