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» Feature selection for linear support vector machines
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CVPR
2003
IEEE
14 years 10 months ago
Kernel Principal Angles for Classification Machines with Applications to Image Sequence Interpretation
We consider the problem of learning with instances defined over a space of sets of vectors. We derive a new positive definite kernel f(A B) defined over pairs of matrices A B base...
Lior Wolf, Amnon Shashua
IJCNN
2006
IEEE
14 years 2 months ago
P-SVM Variable Selection for Discovering Dependencies Between Genetic and Brain Imaging Data
— The joint analysis of genetic and brain imaging data is the key to understand the genetic underpinnings of brain dysfunctions in several psychiatric diseases known to have a st...
Johannes Mohr, Imke Puis, Jana Wrase, Sepp Hochrei...
INTERSPEECH
2010
13 years 2 months ago
Brno university of technology system for interspeech 2010 paralinguistic challenge
This paper describes Brno University of Technology (BUT) system for the Interspeech 2010 Paralinguistic Challenge. Our submitted systems for the Age- and Gender-Sub-Challenges emp...
Marcel Kockmann, Lukas Burget, Jan Cernocký
ECCV
2000
Springer
14 years 9 months ago
Learning to Recognize 3D Objects with SNoW
This paper describes a novel view-based learning algorithm for 3D object recognition from 2D images using a network of linear units. The SNoW learning architecture is a sparse netw...
Ming-Hsuan Yang, Dan Roth, Narendra Ahuja
ICANN
2007
Springer
13 years 11 months ago
Resilient Approximation of Kernel Classifiers
Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...
Thorsten Suttorp, Christian Igel