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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...
IJON
2011
158views more  IJON 2011»
13 years 2 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
IJCNN
2006
IEEE
14 years 2 months ago
Learning the Kernel in Mahalanobis One-Class Support Vector Machines
— In this paper, we show that one-class SVMs can also utilize data covariance in a robust manner to improve performance. Furthermore, by constraining the desired kernel function ...
Ivor W. Tsang, James T. Kwok, Shutao Li
ICCV
2011
IEEE
12 years 8 months ago
Viewpoint-Aware Object Detection and Pose Estimation
We describe an approach to category-level detection and viewpoint estimation for rigid 3D objects from single 2D images. In contrast to many existing methods, we directly integrat...
Daniel Glasner, Meirav Galun, Sharon Alpert, Ronen...
ICALT
2007
IEEE
14 years 2 months ago
The PLExus Prototype: A PLE realized as Topic Maps
The article presents the PLExus prototype, a Personal Learning Environment based on the semantic technology of topic maps. Semantic-based navigation in e-learning will enable vari...
Line Kolås, Arvid Staupe