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ICCV
2003
IEEE
15 years 5 days ago
Feature Selection for Unsupervised and Supervised Inference: the Emergence of Sparsity in a Weighted-based Approach
The problem of selecting a subset of relevant features in a potentially overwhelming quantity of data is classic and found in many branches of science. Examples in computer vision...
Lior Wolf, Amnon Shashua
ICIP
2003
IEEE
14 years 12 months ago
Feature selection for unsupervised discovery of statistical temporal structures in video
We present algorithms for automatic feature selection for unsupervised structure discovery from video sequences. Feature selection in this scenario is hard because of the absence ...
Lexing Xie, Shih-Fu Chang, Ajay Divakaran, Huifang...
CLEF
2006
Springer
14 years 2 months ago
Medical Image Annotation and Retrieval Using Visual Features
In this article, we present the algorithms and results of our participation in the medical image annotation and retrieval tasks of ImageCLEFmed 2006. We exploit both global featur...
Jing Liu, Yang Hu, Mingjing Li, Songde Ma, Wei-Yin...
PAA
2007
13 years 9 months ago
Pairwise feature evaluation for constructing reduced representations
Feature selection methods are often used to determine a small set of informative features that guarantee good classification results. Such procedures usually consist of two compon...
Artsiom Harol, Carmen Lai, Elzbieta Pekalska, Robe...
BMCBI
2010
96views more  BMCBI 2010»
13 years 10 months ago
sdef: an R package to synthesize lists of significant features in related experiments
Background: In microarray studies researchers are often interested in the comparison of relevant quantities between two or more similar experiments, involving different treatments...
Marta Blangiardo, Alberto Cassese, Sylvia Richards...