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COLT
1999
Springer
15 years 2 months ago
1999
Springer
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
NIPS
1998
14 years 11 months ago
1998
Training a Support Vector Machine (SVM) requires the solution of a very large quadratic programming (QP) problem. This paper proposes an algorithm for training SVMs: Sequential Mi...
ICML
2010
IEEE
14 years 11 months ago
2010
IEEE
We develop a penalized kernel smoothing method for the problem of selecting nonzero elements of the conditional precision matrix, known as conditional covariance selection. This p...
ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
In high-dimensional classification problems it is infeasible to include enough training samples to cover the class regions densely. Irregularities in the resulting sparse sample d...
BMCBI
2010
14 years 10 months ago
2010
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...