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» Training of Support Vector Machines with Mahalanobis Kernels
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GECCO
2007
Springer
184views Optimization» more  GECCO 2007»
15 years 1 months ago
Evolving kernels for support vector machine classification
While support vector machines (SVMs) have shown great promise in supervised classification problems, researchers have had to rely on expert domain knowledge when choosing the SVM&...
Keith Sullivan, Sean Luke
83
Voted
ICDM
2009
IEEE
160views Data Mining» more  ICDM 2009»
15 years 4 months ago
Fast Online Training of Ramp Loss Support Vector Machines
—A fast online algorithm OnlineSVMR for training Ramp-Loss Support Vector Machines (SVMR s) is proposed. It finds the optimal SVMR for t+1 training examples using SVMR built on t...
Zhuang Wang, Slobodan Vucetic
ML
2010
ACM
181views Machine Learning» more  ML 2010»
14 years 8 months ago
Decomposing the tensor kernel support vector machine for neuroscience data with structured labels
Abstract The tensor kernel has been used across the machine learning literature for a number of purposes and applications, due to its ability to incorporate samples from multiple s...
David R. Hardoon, John Shawe-Taylor
IJON
2006
119views more  IJON 2006»
14 years 9 months ago
Support vector machine for functional data classification
Abstract. Functional data analysis is a growing research field and numerous works present a generalization of the classical statistical methods to function classification or regres...
Fabrice Rossi, Nathalie Villa
SDM
2009
SIAM
119views Data Mining» more  SDM 2009»
15 years 6 months ago
Twin Vector Machines for Online Learning on a Budget.
This paper proposes Twin Vector Machine (TVM), a constant space and sublinear time Support Vector Machine (SVM) algorithm for online learning. TVM achieves its favorable scaling b...
Zhuang Wang, Slobodan Vucetic