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» Semi-supervised Discriminant Analysis
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ECML
2005
Springer
14 years 3 months ago
Annealed Discriminant Analysis
Abstract. Motivated by the analogies to statistical physics, the deterministic annealing (DA) method has successfully been demonstrated in a variety of application. In this paper, ...
Gang Wang, Zhihua Zhang, Frederick H. Lochovsky
NIPS
2004
13 years 11 months ago
Efficient Kernel Discriminant Analysis via QR Decomposition
Linear Discriminant Analysis (LDA) is a well-known method for feature extraction and dimension reduction. It has been used widely in many applications such as face recognition. Re...
Tao Xiong, Jieping Ye, Qi Li, Ravi Janardan, Vladi...
PR
2008
129views more  PR 2008»
13 years 9 months ago
A comparison of generalized linear discriminant analysis algorithms
7 Linear discriminant analysis (LDA) is a dimension reduction method which finds an optimal linear transformation that maximizes the class separability. However, in undersampled p...
Cheong Hee Park, Haesun Park
FGR
2011
IEEE
272views Biometrics» more  FGR 2011»
13 years 1 months ago
Adaptive discriminant analysis for face recognition from single sample per person
—Discriminant analysis, especially Fisherface and its numerous variants, have achieved great success in face recognition. However, these methods fail to work for face recognition...
Meina Kan, Shiguang Shan, Yu Su, Xilin Chen, Wen G...
IDEAL
2005
Springer
14 years 3 months ago
Kernel Biased Discriminant Analysis Using Histogram Intersection Kernel for Content-Based Image Retrieval
It is known that no single descriptor is powerful enough to encompass all aspects of image content, i.e. each feature extraction method has its own view of the image content. A pos...
Lin Mei, Gerd Brunner, Lokesh Setia, Hans Burkhard...