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CIARP
2006
Springer
13 years 11 months ago
Oscillating Feature Subset Search Algorithm for Text Categorization
Abstract. A major characteristic of text document categorization problems is the extremely high dimensionality of text data. In this paper we explore the usability of the Oscillati...
Jana Novovicová, Petr Somol, Pavel Pudil
IJON
2008
121views more  IJON 2008»
13 years 7 months ago
Locality sensitive semi-supervised feature selection
In many computer vision tasks like face recognition and image retrieval, one is often confronted with high-dimensional data. Procedures that are analytically or computationally ma...
Jidong Zhao, Ke Lu, Xiaofei He
CVPR
2006
IEEE
14 years 9 months ago
Unsupervised Learning of Categories from Sets of Partially Matching Image Features
We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
Kristen Grauman, Trevor Darrell
SDM
2012
SIAM
216views Data Mining» more  SDM 2012»
11 years 10 months ago
Feature Selection "Tomography" - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable
:  Feature Selection “Tomography” - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable George Forman HP Laboratories HPL-2010-19R1 Feature selection; ...
George Forman
ICML
2003
IEEE
14 years 8 months ago
Unsupervised Learning with Permuted Data
We consider the problem of unsupervised learning from a matrix of data vectors where in each row the observed values are randomly permuted in an unknown fashion. Such problems ari...
Sergey Kirshner, Sridevi Parise, Padhraic Smyth