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» Tangent Distance Kernels for Support Vector Machines
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NIPS
2008
13 years 9 months ago
Support Vector Machines with a Reject Option
We consider the problem of binary classification where the classifier may abstain instead of classifying each observation. The Bayes decision rule for this setup, known as Chow�...
Yves Grandvalet, Alain Rakotomamonjy, Joseph Keshe...
PR
2007
104views more  PR 2007»
13 years 7 months ago
Optimizing resources in model selection for support vector machine
Tuning SVM hyperparameters is an important step in achieving a high-performance learning machine. It is usually done by minimizing an estimate of generalization error based on the...
Mathias M. Adankon, Mohamed Cheriet
ECAI
2004
Springer
14 years 28 days ago
A Generalized Quadratic Loss for Support Vector Machines
The standard SVM formulation for binary classification is based on the Hinge loss function, where errors are considered not correlated. Due to this, local information in the featu...
Filippo Portera, Alessandro Sperduti
SAC
2009
ACM
14 years 2 months ago
Music retrieval based on a multi-samples selection strategy for support vector machine active learning
In active learning based music retrieval systems, providing multiple samples to the user for feedback is very necessary. In this paper, we present a new multi-samples selection st...
Tian-Jiang Wang, Gang Chen, Perfecto Herrera
ICIC
2005
Springer
14 years 1 months ago
Signature Verification Using Wavelet Transform and Support Vector Machine
In this paper, we propose a novel on-line handwritten signature verification method. Firstly, the pen-position parameters of the on-line signature are decomposed into multiscale si...
Hong-Wei Ji, Zhong-Hua Quan