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DATAMINE
1998
145views more  DATAMINE 1998»
13 years 6 months ago
A Tutorial on Support Vector Machines for Pattern Recognition
The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and non-...
Christopher J. C. Burges
ICML
2007
IEEE
14 years 7 months ago
Solving multiclass support vector machines with LaRank
Optimization algorithms for large margin multiclass recognizers are often too costly to handle ambitious problems with structured outputs and exponential numbers of classes. Optim...
Antoine Bordes, Jason Weston, Léon Bottou, ...
ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
13 years 8 months ago
Feature Selection for Nonlinear Kernel Support Vector Machines
An easily implementable mixed-integer algorithm is proposed that generates a nonlinear kernel support vector machine (SVM) classifier with reduced input space features. A single ...
Olvi L. Mangasarian, Gang Kou
NIPS
1998
13 years 7 months ago
Using Analytic QP and Sparseness to Speed Training of Support Vector Machines
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...
John C. Platt
CNSM
2010
13 years 3 months ago
Risk management in VoIP infrastructures using support vector machines
Telephony over IP is exposed to multiple security threats. Conventional protection mechanisms do not fit into the highly dynamic, open and large-scale settings of VoIP infrastructu...
Mohamed Nassar, Oussema Dabbebi, Remi Badonnel, Ol...