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» Feature selection in a kernel space
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CIARP
2010
Springer
13 years 7 months ago
A New Algorithm for Training SVMs Using Approximate Minimal Enclosing Balls
Abstract. It has been shown that many kernel methods can be equivalently formulated as minimal-enclosing-ball (MEB) problems in certain feature space. Exploiting this reduction eff...
Emanuele Frandi, Maria Grazia Gasparo, Stefano Lod...
COLT
2008
Springer
13 years 12 months ago
Dimension and Margin Bounds for Reflection-invariant Kernels
A kernel over the Boolean domain is said to be reflection-invariant, if its value does not change when we flip the same bit in both arguments. (Many popular kernels have this prop...
Thorsten Doliwa, Michael Kallweit, Hans-Ulrich Sim...
CVPR
2008
IEEE
15 years 2 days ago
Discovering class specific composite features through discriminative sampling with Swendsen-Wang Cut
This paper proposes a novel approach to discover a set of class specific "composite features" as the feature pool for the detection and classification of complex objects...
Feng Han, Ying Shan, Harpreet S. Sawhney, Rakesh K...
DAC
2003
ACM
14 years 11 months ago
Using estimates from behavioral synthesis tools in compiler-directed design space exploration
This paper considers the role of performance and area estimates from behavioral synthesis in design space exploration. We have developed a compilation system that automatically ma...
Byoungro So, Pedro C. Diniz, Mary W. Hall
CVPR
2009
IEEE
14 years 1 months ago
Nonlinear Nonnegative Component Analysis
In this paper general solutions for Nonlinear Nonnegative Component Analysis for data representation and recognition are proposed. That is, motivated by a combination of the Nonne...
Stefanos Zafeiriou, Maria Petrou