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» Covering Numbers for Support Vector Machines
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ICIP
2002
IEEE
16 years 1 months ago
Learning a decision boundary for face detection
This paper describes a pattern classification approach for detecting frontal-view faces via learning a decision boundary. The classification can be achieved either by explicit est...
Tae-Kyun Kim, Donggeon Kong, Sang Ryong Kim
BMCBI
2008
138views more  BMCBI 2008»
14 years 12 months ago
Application of nonnegative matrix factorization to improve profile-profile alignment features for fold recognition and remote ho
Background: Nonnegative matrix factorization (NMF) is a feature extraction method that has the property of intuitive part-based representation of the original features. This uniqu...
Inkyung Jung, Jaehyung Lee, Soo-Young Lee, Dongsup...
CIBCB
2005
IEEE
15 years 5 months ago
Feature Selection for Microarray Data Using Least Squares SVM and Particle Swarm Optimization
Feature selection is an important preprocessing technique for many pattern recognition problems. When the number of features is very large while the number of samples is relatively...
E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao
DAGM
2006
Springer
15 years 3 months ago
Feature Selection for Automatic Image Annotation
Automatic image annotation empowers the user to search an image database using keywords, which is often a more practical option than a query-by-example approach. In this work, we p...
Lokesh Setia, Hans Burkhardt
JMLR
2006
123views more  JMLR 2006»
14 years 11 months ago
Adaptive Prototype Learning Algorithms: Theoretical and Experimental Studies
In this paper, we propose a number of adaptive prototype learning (APL) algorithms. They employ the same algorithmic scheme to determine the number and location of prototypes, but...
Fu Chang, Chin-Chin Lin, Chi-Jen Lu