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TNN
2008
182views more  TNN 2008»
13 years 7 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...
ICML
2007
IEEE
14 years 8 months ago
Support cluster machine
For large-scale classification problems, the training samples can be clustered beforehand as a downsampling pre-process, and then only the obtained clusters are used for training....
Bin Li, Mingmin Chi, Jianping Fan, Xiangyang Xue
ICML
2004
IEEE
14 years 8 months ago
Distribution kernels based on moments of counts
Many applications in text and speech processing require the analysis of distributions of variable-length sequences. We recently introduced a general kernel framework, rational ker...
Corinna Cortes, Mehryar Mohri
ICPR
2004
IEEE
14 years 8 months ago
Corner Detection Using Support Vector Machines
A support vector machine based algorithm for corner detection is presented. It is based on computing the direction of maximum gray-level change for each edge pixel in an image, an...
Malay K. Kundu, Minakshi Banerjee, Pabitra Mitra
ADMA
2005
Springer
134views Data Mining» more  ADMA 2005»
13 years 9 months ago
An LZ78 Based String Kernel
We develop the notion of normalized information distance (NID) [7] into a kernel distance suitable for use with a Support Vector Machine classifier, and demonstrate its use for an...
Ming Li, Ronan Sleep