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» On-line support vector machines and optimization strategies
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CVPR
2006
IEEE
15 years 1 months ago
Region-based Image Annotation using Asymmetrical Support Vector Machine-based Multiple-Instance Learning
In region-based image annotation, keywords are usually associated with images instead of individual regions in the training data set. This poses a major challenge for any learning...
Changbo Yang, Ming Dong, Jing Hua
JMLR
2010
115views more  JMLR 2010»
14 years 4 months ago
Fast and Scalable Local Kernel Machines
A computationally efficient approach to local learning with kernel methods is presented. The Fast Local Kernel Support Vector Machine (FaLK-SVM) trains a set of local SVMs on redu...
Nicola Segata, Enrico Blanzieri
IJCAI
2007
14 years 11 months ago
Prediction of Probability of Survival in Critically Ill Patients Optimizing the Area under the ROC Curve
: This article presents the method of Support Vectors Machines (SVM) for predicting probability of survival in critically ill patients by using Platt’s method to fit a sigmoid1 ....
Oscar Luaces, José Ramón Quevedo, Fr...
PAMI
2010
122views more  PAMI 2010»
14 years 8 months ago
Domain Adaptation Problems: A DASVM Classification Technique and a Circular Validation Strategy
—This paper addresses pattern classification in the framework of domain adaptation by considering methods that solve problems in which training data are assumed to be available o...
Lorenzo Bruzzone, Mattia Marconcini
75
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ICML
2008
IEEE
15 years 10 months ago
Training SVM with indefinite kernels
Similarity matrices generated from many applications may not be positive semidefinite, and hence can't fit into the kernel machine framework. In this paper, we study the prob...
Jianhui Chen, Jieping Ye