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» Optimally Regularised Kernel Fisher Discriminant Analysis
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PAMI
2008
162views more  PAMI 2008»
14 years 11 months ago
Bayes Optimality in Linear Discriminant Analysis
We present an algorithm which provides the one-dimensional subspace where the Bayes error is minimized for the C class problem with homoscedastic Gaussian distributions. Our main ...
Onur C. Hamsici, Aleix M. Martínez
PAMI
2006
132views more  PAMI 2006»
14 years 11 months ago
Capitalize on Dimensionality Increasing Techniques for Improving Face Recognition Grand Challenge Performance
This paper presents a novel pattern recognition framework by capitalizing on dimensionality increasing techniques. In particular, the framework integrates Gabor image representatio...
Chengjun Liu
CVPR
2010
IEEE
15 years 7 months ago
Pareto Discriminant Analysis
Linear Discriminant Analysis (LDA) is a popular tool for multiclass discriminative dimensionality reduction. However, LDA suffers from two major problems: (1) It only optimizes th...
Karim Abou-Moustafa, Fernando De la Torre, Frank F...
SIAMJO
2008
104views more  SIAMJO 2008»
14 years 11 months ago
A Minimax Theorem with Applications to Machine Learning, Signal Processing, and Finance
This paper concerns a fractional function of the form xT a/ xT Bx, where B is positive definite. We consider the game of choosing x from a convex set, to maximize the function, an...
Seung-Jean Kim, Stephen P. Boyd
PR
2008
129views more  PR 2008»
14 years 11 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