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TNN
2008
182views more  TNN 2008»
15 years 17 days 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...
DATAMINE
1998
145views more  DATAMINE 1998»
15 years 11 days ago
A Tutorial on Support Vector Machines for Pattern Recognition
The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and non-...
Christopher J. C. Burges
EMNLP
2011
14 years 13 days ago
Relation Extraction with Relation Topics
This paper describes a novel approach to the semantic relation detection problem. Instead of relying only on the training instances for a new relation, we leverage the knowledge l...
Chang Wang, James Fan, Aditya Kalyanpur, David Gon...
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ICPR
2008
IEEE
16 years 1 months ago
Generalized Nonlinear Discriminant Analysis
A Generalized Nonlinear Discriminant Analysis (GNDA) method is proposed, which implements Fisher discriminant analysis in a nonlinear mapping space. Linear discriminant analysis i...
Hua Zhang, Li Zhang, Licheng Jiao, Weida Zhou
MICCAI
2005
Springer
16 years 1 months ago
A Physical Model for DT-MRI Based Connectivity Map Computation
In this study we address the problem of extracting a robust connectivity metric for brain white matter. We defined the connectivity problem as an energy minimization task, by assoc...
Burak Acar, Erdem Yörük, Roland Bammer