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MICCAI
2002
Springer
15 years 10 months ago
Comparative Exudate Classification Using Support Vector Machines and Neural Networks
After segmenting candidate exudates regions in colour retinal images we present and compare two methods for their classification. The Neural Network based approach performs margina...
Alireza Osareh, Majid Mirmehdi, Barry T. Thomas, R...
SDM
2007
SIAM
81views Data Mining» more  SDM 2007»
14 years 11 months ago
A PAC Bound for Approximate Support Vector Machines
We study a class of algorithms that speed up the training process of support vector machines (SVMs) by returning an approximate SVM. We focus on algorithms that reduce the size of...
Dongwei Cao, Daniel Boley
AUTOMATICA
2006
150views more  AUTOMATICA 2006»
14 years 9 months ago
Enlarging the terminal region of nonlinear model predictive control using the support vector machine method
In this paper, Receding Horizon Model Predictive Control (RHMPC) of nonlinear systems subject to input and state constraints is considered. We propose to estimate the terminal reg...
Chong Jin Ong, Dan Sui, Elmer G. Gilbert
SIGKDD
2000
139views more  SIGKDD 2000»
14 years 9 months ago
Support Vector Machines: Hype or Hallelujah?
Support Vector Machines (SVMs) and related kernel methods have become increasingly popular tools for data mining tasks such as classification, regression, and novelty detection. T...
Kristin P. Bennett, Colin Campbell
JMLR
2008
123views more  JMLR 2008»
14 years 9 months ago
Optimization Techniques for Semi-Supervised Support Vector Machines
Due to its wide applicability, the problem of semi-supervised classification is attracting increasing attention in machine learning. Semi-Supervised Support Vector Machines (S3VMs...
Olivier Chapelle, Vikas Sindhwani, S. Sathiya Keer...