709 search results - page 49 / 142 » Dynamically Adapting Kernels in Support Vector Machines |
138
Voted
CORR
2006
Springer
15 years 3 months ago
2006
Springer
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
119
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IPPS
2006
IEEE
15 years 9 months ago
2006
IEEE
High-performance computing clusters running longlived tasks currently cannot have kernel software updates applied to them without causing system downtime. These clusters miss oppo...
139
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AVBPA
2005
Springer
15 years 8 months ago
2005
Springer
A novel nonlinear discriminant analysis method, Kernelized Decision Boundary Analysis (KDBA), is proposed in our paper, whose Decision Boundary feature vectors are the normal vecto...
125
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SAC
2006
ACM
15 years 9 months ago
2006
ACM
Traditional Data Mining and Knowledge Discovery algorithms assume free access to data, either at a centralized location or in federated form. Increasingly, privacy and security co...
128
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ESANN
2007
15 years 4 months ago
2007
Radial basis function network (RBF) kernels are widely used for support vector machines (SVMs). But for model selection of an SVM, we need to optimize the kernel parameter and the ...