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» Possibilistic Clustering in Feature Space
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CORR
2012
Springer
198views Education» more  CORR 2012»
12 years 3 months ago
Lipschitz Parametrization of Probabilistic Graphical Models
We show that the log-likelihood of several probabilistic graphical models is Lipschitz continuous with respect to the ￿p-norm of the parameters. We discuss several implications ...
Jean Honorio
IVC
2006
154views more  IVC 2006»
13 years 7 months ago
Manifold based analysis of facial expression
We propose a novel approach for modeling, tracking and recognizing facial expressions. Our method works on a low dimensional expression manifold, which is obtained by Isomap embed...
Ya Chang, Changbo Hu, Rogerio Feris, Matthew Turk
BMCBI
2007
166views more  BMCBI 2007»
13 years 7 months ago
How to decide which are the most pertinent overly-represented features during gene set enrichment analysis
Background: The search for enriched features has become widely used to characterize a set of genes or proteins. A key aspect of this technique is its ability to identify correlati...
Roland Barriot, David J. Sherman, Isabelle Dutour
MIR
2003
ACM
174views Multimedia» more  MIR 2003»
14 years 1 months ago
Content-based image retrieval by clustering
In a typical content-based image retrieval (CBIR) system, query results are a set of images sorted by feature similarities with respect to the query. However, images with high fea...
Yixin Chen, James Ze Wang, Robert Krovetz
ICPR
2008
IEEE
14 years 9 months ago
Unsupervised image embedding using nonparametric statistics
Embedding images into a low dimensional space has a wide range of applications: visualization, clustering, and pre-processing for supervised learning. Traditional dimension reduct...
Guobiao Mei, Christian R. Shelton