93 search results - page 7 / 19 » Maximal Discrepancy for Support Vector Machines |
IJCNN
2006
IEEE
14 years 1 months ago
2006
IEEE
— Area Under the ROC Curve (AUC) is often used to evaluate ranking performance in binary classification problems. Several researchers have approached AUC optimization by approxi...
NIPS
2000
13 years 8 months ago
2000
A new incremental learning algorithm is described which approximates the maximal margin hyperplane w.r.t. norm p 2 for a set of linearly separable data. Our algorithm, called alm...
JMLR
2010
13 years 2 months ago
2010
This paper proposes a novel algorithm for semisupervised learning. This algorithm learns graph cuts that maximize the margin with respect to the labels induced by the harmonic fun...
CVPR
2003
IEEE
14 years 9 months ago
2003
IEEE
We introduce a new classification algorithm based on the concept of Symmetric Maximized Minimal distance in Subspace (SMMS). Given the training data of authentic samples and impos...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
We extend Support Vector Machines to input spaces that are sets by ensuring that the classifier is invariant to permutations of subelements within each input. Such permutations in...