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» Boosting margin based distance functions for clustering
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ICALP
2009
Springer
14 years 9 months ago
Correlation Clustering Revisited: The "True" Cost of Error Minimization Problems
Correlation Clustering was defined by Bansal, Blum, and Chawla as the problem of clustering a set of elements based on a possibly inconsistent binary similarity function between e...
Nir Ailon, Edo Liberty
ICCV
2007
IEEE
14 years 10 months ago
Locally Smooth Metric Learning with Application to Image Retrieval
In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
Dit-Yan Yeung, Hong Chang
DIS
2001
Springer
14 years 1 months ago
Functional Trees
In the context of classification problems, algorithms that generate multivariate trees are able to explore multiple representation languages by using decision tests based on a com...
Joao Gama
BMCBI
2005
198views more  BMCBI 2005»
13 years 8 months ago
Clustering protein sequences with a novel metric transformed from sequence similarity scores and sequence alignments with neural
Background: The sequencing of the human genome has enabled us to access a comprehensive list of genes (both experimental and predicted) for further analysis. While a majority of t...
Qicheng Ma, Gung-Wei Chirn, Richard Cai, Joseph D....
ICPR
2008
IEEE
14 years 3 months ago
A fuzzy c-means algorithm using a correlation metrics and gene ontology
A fuzzy c-means algorithm was adapted for analyzing microarray data. The adaptation consisted of initialization of fuzzy centroids using gene ontology information and the use of P...
Mingrui Zhang, Terry M. Therneau, Michael A. McKen...