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» Generalized Discriminant Analysis Using a Kernel Approach
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ESANN
2007
13 years 9 months ago
Interval discriminant analysis using support vector machines
Imprecision, incompleteness, prior knowledge or improved learning speed can motivate interval–represented data. Most approaches for SVM learning of interval data use local kernel...
Cecilio Angulo, Davide Anguita, Luis Gonzál...
WACV
2012
IEEE
12 years 3 months ago
Kernel analysis over Riemannian manifolds for visual recognition of actions, pedestrians and textures
A convenient way of analysing Riemannian manifolds is to embed them in Euclidean spaces, with the embedding typically obtained by flattening the manifold via tangent spaces. This...
Mehrtash Tafazzoli Harandi, Conrad Sanderson, Arno...
ICA
2007
Springer
14 years 1 months ago
On Separation of Signal Sources Using Kernel Estimates of Probability Densities
The discussion in this paper revolves around the notion of separation problems. The latter can be thought of as a unifying concept which includes a variety of important problems in...
Oleg V. Michailovich, Douglas Wiens
PR
2007
145views more  PR 2007»
13 years 7 months ago
Face recognition using a kernel fractional-step discriminant analysis algorithm
Feature extraction is among the most important problems in face recognition systems. In this paper, we propose an enhanced kernel discriminant analysis (KDA) algorithm called kern...
Guang Dai, Dit-Yan Yeung, Yuntao Qian
CVPR
2012
IEEE
11 years 10 months ago
Generalized Multiview Analysis: A discriminative latent space
This paper presents a general multi-view feature extraction approach that we call Generalized Multiview Analysis or GMA. GMA has all the desirable properties required for cross-vi...
Abhishek Sharma, Abhishek Kumar, Hal Daumé ...