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» Dynamically Adapting Kernels in Support Vector Machines
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ICANN
2007
Springer
14 years 2 months ago
Incremental and Decremental Learning for Linear Support Vector Machines
Abstract. We present a method to find the exact maximal margin hyperplane for linear Support Vector Machines when a new (existing) component is added (removed) to (from) the inner...
Enrique Romero, Ignacio Barrio, Lluís Belan...
NIPS
2004
13 years 9 months ago
The Entire Regularization Path for the Support Vector Machine
The support vector machine (SVM) is a widely used tool for classification. Many efficient implementations exist for fitting a two-class SVM model. The user has to supply values fo...
Trevor Hastie, Saharon Rosset, Robert Tibshirani, ...
JMLR
2008
110views more  JMLR 2008»
13 years 8 months ago
Estimating the Confidence Interval for Prediction Errors of Support Vector Machine Classifiers
Support vector machine (SVM) is one of the most popular and promising classification algorithms. After a classification rule is constructed via the SVM, it is essential to evaluat...
Bo Jiang, Xuegong Zhang, Tianxi Cai
IFIP7
2001
Springer
137views Optimization» more  IFIP7 2001»
14 years 27 days ago
Data Mining via Support Vector Machines
Support vector machines (SVMs) have played a key role in broad classes of problems arising in various fields. Much more recently, SVMs have become the tool of choice for problems...
Olvi L. Mangasarian
PAMI
2006
128views more  PAMI 2006»
13 years 8 months ago
Multisurface Proximal Support Vector Machine Classification via Generalized Eigenvalues
A new approach to support vector machine (SVM) classification is proposed wherein each of two data sets are proximal to one of two distinct planes that are not parallel to each oth...
Olvi L. Mangasarian, Edward W. Wild