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» Support Vector Machines: Theory and Applications
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ICCV
2009
IEEE
13 years 6 months ago
Kernel map compression using generalized radial basis functions
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
Omar Arif, Patricio A. Vela
JCP
2006
102views more  JCP 2006»
13 years 8 months ago
Efficient Formulations for 1-SVM and their Application to Recommendation Tasks
The present paper proposes new approaches for recommendation tasks based on one-class support vector machines (1-SVMs) with graph kernels generated from a Laplacian matrix. We intr...
Yasutoshi Yajima, Tien-Fang Kuo
IJISTA
2007
124views more  IJISTA 2007»
13 years 8 months ago
Incremental learning for spoken affect classification and its application in call-centres
: This paper introduces a system for real-time incremental learning in a call-centre environment. The classifier used is a Support Vector Machine (SVM) and it is applied to telepho...
Donn Morrison, Ruili Wang, W. L. Xu, Liyanage C. D...
TIFS
2008
194views more  TIFS 2008»
13 years 8 months ago
Detection of Double-Compression in JPEG Images for Applications in Steganography
This paper presents a method for detection of double JPEG compression and a maximum likelihood estimator of the primary quality factor. These methods are essential for construction...
Tomás Pevný, Jessica J. Fridrich
ICANN
2007
Springer
14 years 2 months ago
Unbiased SVM Density Estimation with Application to Graphical Pattern Recognition
Abstract. Classification of structured data (i.e., data that are represented as graphs) is a topic of interest in the machine learning community. This paper presents a different,...
Edmondo Trentin, Ernesto Di Iorio