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NIPS
2003
13 years 6 months ago
Feature Selection in Clustering Problems
A novel approach to combining clustering and feature selection is presented. It implements a wrapper strategy for feature selection, in the sense that the features are directly se...
Volker Roth, Tilman Lange
NIPS
2007
13 years 6 months ago
Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity Recognition
We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs). In real-world applications suc...
Maryam Mahdaviani, Tanzeem Choudhury
BMCBI
2008
160views more  BMCBI 2008»
13 years 5 months ago
Feature selection environment for genomic applications
Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e....
Fabrício Martins Lopes, David Correa Martin...
ICCV
2007
IEEE
14 years 7 months ago
Extracting Spatiotemporal Interest Points using Global Information
Local spatiotemporal features or interest points provide compact but descriptive representations for efficient video analysis and motion recognition. Current local feature extract...
Shu-Fai Wong, Roberto Cipolla
KDD
2006
ACM
150views Data Mining» more  KDD 2006»
14 years 5 months ago
Maximally informative k-itemsets and their efficient discovery
In this paper we present a new approach to mining binary data. We treat each binary feature (item) as a means of distinguishing two sets of examples. Our interest is in selecting ...
Arno J. Knobbe, Eric K. Y. Ho