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» Tangent Distance Kernels for Support Vector Machines
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JMLR
2006
143views more  JMLR 2006»
13 years 7 months ago
Consistency and Convergence Rates of One-Class SVMs and Related Algorithms
We determine the asymptotic behaviour of the function computed by support vector machines (SVM) and related algorithms that minimize a regularized empirical convex loss function i...
Régis Vert, Jean-Philippe Vert
JMLR
2002
89views more  JMLR 2002»
13 years 7 months ago
A Robust Minimax Approach to Classification
When constructing a classifier, the probability of correct classification of future data points should be maximized. We consider a binary classification problem where the mean and...
Gert R. G. Lanckriet, Laurent El Ghaoui, Chiranjib...
ICCV
2011
IEEE
12 years 7 months ago
Struck: Structured Output Tracking with Kernels
Adaptive tracking-by-detection methods are widely used in computer vision for tracking arbitrary objects. Current approaches treat the tracking problem as a classification task a...
Sam Hare, Amir Saffari, Philip H.S. Torr
MIR
2006
ACM
141views Multimedia» more  MIR 2006»
14 years 1 months ago
Mining temporal patterns of movement for video content classification
Scalable approaches to video content classification are limited by an inability to automatically generate representations of events ode abstract temporal structure. This paper pre...
Michael Fleischman, Philip DeCamp, Deb Roy
NECO
2000
190views more  NECO 2000»
13 years 7 months ago
Generalized Discriminant Analysis Using a Kernel Approach
We present a new method that we call Generalized Discriminant Analysis (GDA) to deal with nonlinear discriminant analysis using kernel function operator. The underlying theory is ...
G. Baudat, Fatiha Anouar