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» Feature selection for linear support vector machines
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ICML
2005
IEEE
14 years 8 months ago
Building Sparse Large Margin Classifiers
This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The ad...
Bernhard Schölkopf, Gökhan H. Bakir, Min...
ICML
2010
IEEE
13 years 6 months ago
The Margin Perceptron with Unlearning
We introduce into the classical Perceptron algorithm with margin a mechanism of unlearning which in the course of the regular update allows for a reduction of possible contributio...
Constantinos Panagiotakopoulos, Petroula Tsampouka
ECCV
2002
Springer
14 years 9 months ago
Learning to Parse Pictures of People
The detection of people is one of the foremost problems for indexing, browsing and retrieval of video. The main difficulty is the large appearance variations caused by action, clot...
Rémi Ronfard, Cordelia Schmid, Bill Triggs
ICASSP
2009
IEEE
14 years 2 months ago
Lattice-based MLLR for speaker recognition
Maximum-Likelihod Linear Regression (MLLR) transform coefficients have shown to be useful features for text-independent speaker recognition systems. These use MLLR coefficients ...
Marc Ferras, Claude Barras, Jean-Luc Gauvain
ICASSP
2008
IEEE
14 years 2 months ago
A multi-class MLLR kernel for SVM speaker recognition
Speaker recognition using support vector machines (SVMs) with features derived from generative models has been shown to perform well. Typically, a universal background model (UBM)...
Zahi N. Karam, William M. Campbell