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» Introduction to Statistical Learning Theory
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JMLR
2006
107views more  JMLR 2006»
13 years 7 months ago
Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss
The consistency of classification algorithm plays a central role in statistical learning theory. A consistent algorithm guarantees us that taking more samples essentially suffices...
Di-Rong Chen, Tao Sun
SIGKDD
2000
139views more  SIGKDD 2000»
13 years 7 months ago
Support Vector Machines: Hype or Hallelujah?
Support Vector Machines (SVMs) and related kernel methods have become increasingly popular tools for data mining tasks such as classification, regression, and novelty detection. T...
Kristin P. Bennett, Colin Campbell
ECML
2006
Springer
13 years 11 months ago
The Minimum Volume Covering Ellipsoid Estimation in Kernel-Defined Feature Spaces
Minimum volume covering ellipsoid estimation is important in areas such as systems identification, control, video tracking, sensor management, and novelty detection. It is well kno...
Alexander N. Dolia, Tijl De Bie, Christopher J. Ha...
SIBGRAPI
2009
IEEE
14 years 2 months ago
Hermite Interpolation of Implicit Surfaces with Radial Basis Functions
—We present the Hermite radial basis function (HRBF) implicits method to compute a global implicit function which interpolates scattered multivariate Hermite data (unstructured p...
Ives Macedo, Joao Paulo Gois, Luiz Velho
ACL
2009
13 years 5 months ago
A Novel Discourse Parser Based on Support Vector Machine Classification
This paper introduces a new algorithm to parse discourse within the framework of Rhetorical Structure Theory (RST). Our method is based on recent advances in the field of statisti...
David duVerle, Helmut Prendinger