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» A Kernel Method for the Two-Sample Problem
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NIPS
2001
15 years 3 months ago
Minimax Probability Machine
When constructing a classifier, the probability of correct classification of future data points should be maximized. In the current paper this desideratum is translated in a very ...
Gert R. G. Lanckriet, Laurent El Ghaoui, Chiranjib...
JMLR
2008
140views more  JMLR 2008»
15 years 2 months ago
Aggregation of SVM Classifiers Using Sobolev Spaces
This paper investigates statistical performances of Support Vector Machines (SVM) and considers the problem of adaptation to the margin parameter and to complexity. In particular ...
Sébastien Loustau
JMLR
2008
95views more  JMLR 2008»
15 years 2 months ago
Learning Similarity with Operator-valued Large-margin Classifiers
A method is introduced to learn and represent similarity with linear operators in kernel induced Hilbert spaces. Transferring error bounds for vector valued large-margin classifie...
Andreas Maurer
CVPR
2009
IEEE
1528views Computer Vision» more  CVPR 2009»
16 years 6 months ago
Structured Output-Associative Regression
Structured outputs such as multidimensional vectors or graphs are frequently encountered in real world pattern recognition applications such as computer vision, natural language pr...
Liefeng Bo and Cristian Sminchisescu
CVPR
2009
IEEE
15 years 6 months ago
"Who are you?" - Learning person specific classifiers from video
We investigate the problem of automatically labelling faces of characters in TV or movie material with their names, using only weak supervision from automaticallyaligned subtitle ...
Josef Sivic, Mark Everingham, Andrew Zisserman