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» Covering Numbers for Support Vector Machines
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JMLR
2007
101views more  JMLR 2007»
14 years 11 months ago
Noise Tolerant Variants of the Perceptron Algorithm
A large number of variants of the Perceptron algorithm have been proposed and partially evaluated in recent work. One type of algorithm aims for noise tolerance by replacing the l...
Roni Khardon, Gabriel Wachman
ICDAR
2011
IEEE
13 years 11 months ago
Lexicon-Free, Novel Segmentation of Online Handwritten Indic Words
—Research in the field of recognizing unlimited vocabulary, online handwritten Indic words is still in its infancy. Most of the focus so far has been in the area of isolated cha...
Suresh Sundaram, A. G. Ramakrishnan
JMLR
2012
13 years 2 months ago
A metric learning perspective of SVM: on the relation of LMNN and SVM
Support Vector Machines, SVMs, and the Large Margin Nearest Neighbor algorithm, LMNN, are two very popular learning algorithms with quite different learning biases. In this paper...
Huyen Do, Alexandros Kalousis, Jun Wang, Adam Wozn...
COLT
2003
Springer
15 years 5 months ago
Learning from Uncertain Data
The application of statistical methods to natural language processing has been remarkably successful over the past two decades. But, to deal with recent problems arising in this ...
Mehryar Mohri
ICAISC
2004
Springer
15 years 5 months ago
Relevance LVQ versus SVM
Abstract. The support vector machine (SVM) constitutes one of the most successful current learning algorithms with excellent classification accuracy in large real-life problems an...
Barbara Hammer, Marc Strickert, Thomas Villmann