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» Semi-Supervised Support Vector Machines
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ML
2010
ACM
181views Machine Learning» more  ML 2010»
13 years 7 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
ICMLA
2009
13 years 6 months ago
Improving Clinical Relevance in Ensemble Support Vector Machine Models of Radiation Pneumonitis Risk
Patients undergoing thoracic radiation therapy can develop radiation pneumonitis (RP), a potentially fatal inflammation of the lungs. Support vector machines (SVMs), a statistical...
Todd W. Schiller, Yixin Chen, Issam El-Naqa, Josep...
TSMC
2008
106views more  TSMC 2008»
13 years 8 months ago
Two Criteria for Model Selection in Multiclass Support Vector Machines
Abstract--Practical applications call for efficient model selection criteria for multiclass support vector machine (SVM) classification. To solve this problem, this paper develops ...
Lei Wang, Ping Xue, Kap Luk Chan
IJON
2011
158views more  IJON 2011»
13 years 3 months ago
Maximal Discrepancy for Support Vector Machines
Several theoretical methods have been developed in the past years to evaluate the generalization ability of a classifier: they provide extremely useful insights on the learning ph...
Davide Anguita, Alessandro Ghio, Sandro Ridella
COLT
2003
Springer
14 years 2 months ago
Learning with Rigorous Support Vector Machines
We examine the so-called rigorous support vector machine (RSVM) approach proposed by Vapnik (1998). The formulation of RSVM is derived by explicitly implementing the structural ris...
Jinbo Bi, Vladimir Vapnik