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WACV
2005
IEEE
14 years 1 months ago
Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Thomas S. Stepleton, Tai Sing Lee
ESANN
2007
13 years 9 months ago
A new feature selection scheme using data distribution factor for transactional data
A new efficient unsupervised feature selection method is proposed to handle transactional data. The proposed feature selection method introduces a new Data Distribution Factor (DDF...
Piyang Wang, Tommy W. S. Chow
CORR
2008
Springer
118views Education» more  CORR 2008»
13 years 8 months ago
Learning Low-Density Separators
Abstract. We define a novel, basic, unsupervised learning problem learning the the lowest density homogeneous hyperplane separator of an unknown probability distribution. This task...
Shai Ben-David, Tyler Lu, Dávid Pál,...
MVA
2010
130views Computer Vision» more  MVA 2010»
13 years 6 months ago
Neighborhood linear embedding for intrinsic structure discovery
In this paper, an unsupervised learning algorithm, neighborhood linear embedding (NLE), is proposed to discover the intrinsic structures such as neighborhood relationships, global ...
Shuzhi Sam Ge, Feng Guan, Yaozhang Pan, Ai Poh Loh
CVPR
2011
IEEE
13 years 4 months ago
Iterative Quantization: A Procrustean Approach to Learning Binary Codes
This paper addresses the problem of learning similaritypreserving binary codes for efficient retrieval in large-scale image collections. We propose a simple and efficient altern...
Yunchao Gong, Svetlana Lazebnik