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ICML
2003
IEEE
14 years 8 months ago
Incorporating Diversity in Active Learning with Support Vector Machines
In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
Klaus Brinker
SYNASC
2006
IEEE
95views Algorithms» more  SYNASC 2006»
14 years 1 months ago
Evolutionary Support Vector Regression Machines
Evolutionary support vector machines (ESVMs) are a novel technique that assimilates the learning engine of the state-of-the-art support vector machines (SVMs) but evolves the coef...
Ruxandra Stoean, Dumitru Dumitrescu, Mike Preuss, ...
FSS
2007
102views more  FSS 2007»
13 years 7 months ago
Extraction of fuzzy rules from support vector machines
The relationship between support vector machines (SVMs) and Takagi–Sugeno–Kang (TSK) fuzzy systems is shown. An exact representation of SVMs as TSK fuzzy systems is given for ...
Juan Luis Castro, L. D. Flores-Hidalgo, Carlos Jav...
CEC
2007
IEEE
14 years 2 months ago
Concerning the potential of evolutionary support vector machines
— Within the present paper, we put forward a novel hybridization between support vector machines and evolutionary algorithms. Evolutionary support vector machines consider the cl...
Ruxandra Stoean, Mike Preuss, Catalin Stoean, Dumi...
DAGM
2007
Springer
13 years 11 months ago
Greedy-Based Design of Sparse Two-Stage SVMs for Fast Classification
Cascades of classifiers constitute an important architecture for fast object detection. While boosting of simple (weak) classifiers provides an established framework, the design of...
Rezaul Karim, Martin Bergtholdt, Jörg H. Kapp...