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» Training Invariant Support Vector Machines
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ICML
2004
IEEE
15 years 10 months ago
Improving SVM accuracy by training on auxiliary data sources
The standard model of supervised learning assumes that training and test data are drawn from the same underlying distribution. This paper explores an application in which a second...
Pengcheng Wu, Thomas G. Dietterich
ICASSP
2009
IEEE
14 years 7 months ago
Phonological features in discriminative classification of dysarthric speech
In an attempt to overcome problems associated with articulatory limitations and generative models, this work considers the use of phonological features in discriminative models fo...
Frank Rudzicz
ICML
2003
IEEE
15 years 10 months ago
The Set Covering Machine with Data-Dependent Half-Spaces
We examine the set covering machine when it uses data-dependent half-spaces for its set of features and bound its generalization error in terms of the number of training errors an...
Mario Marchand, Mohak Shah, John Shawe-Taylor, Mar...
ICML
2009
IEEE
15 years 10 months ago
A simpler unified analysis of budget perceptrons
The kernel Perceptron is an appealing online learning algorithm that has a drawback: whenever it makes an error it must increase its support set, which slows training and testing ...
Ilya Sutskever
ICIP
2005
IEEE
15 years 11 months ago
Comparison of invariant descriptors for object recognition
This paper deals with the performance evaluation of three object invariant descriptors : Hu moments, Zernike moments and Fourier-Mellin descriptors. Experiments are conducted on a...
Anant Choksuriwong, Bruno Emile, Hélè...