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» The Pre-Image Problem in Kernel Methods
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JMLR
2008
95views more  JMLR 2008»
13 years 8 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»
15 years 28 days 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
14 years 19 days 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
TNN
2008
182views more  TNN 2008»
13 years 8 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
14 years 19 days ago
Controlling overfitting with multi-objective support vector machines
Recently, evolutionary computation has been successfully integrated into statistical learning methods. A Support Vector Machine (SVM) using evolution strategies for its optimizati...
Ingo Mierswa