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ICPR
2004
IEEE
15 years 10 months ago
Optimally Regularised Kernel Fisher Discriminant Analysis
Mika et al. [3] introduce a non-linear formulation of Fisher's linear discriminant, based the now familiar "kernel trick", demonstrating state-of-the-art performanc...
Gavin C. Cawley, Kamel Saadi, Nicola L. C. Talbot
ECCV
2004
Springer
15 years 11 months ago
Multiple View Feature Descriptors from Image Sequences via Kernel Principal Component Analysis
Abstract. We present a method for learning feature descriptors using multiple images, motivated by the problems of mobile robot navigation and localization. The technique uses the ...
Jason Meltzer, Ming-Hsuan Yang, Rakesh Gupta, Stef...
IJCNN
2008
IEEE
15 years 4 months ago
Feature selection based on kernel discriminant analysis for multi-class problems
— We propose a feature selection criterion based on kernel discriminant analysis (KDA) for an -class problem, which finds eigenvectors on which the projected class data are loca...
Tsuneyoshi Ishii, Shigeo Abe
CDC
2009
IEEE
180views Control Systems» more  CDC 2009»
15 years 1 months ago
Robustness analysis for Least Squares kernel based regression: an optimization approach
—In kernel based regression techniques (such as Support Vector Machines or Least Squares Support Vector Machines) it is hard to analyze the influence of perturbed inputs on the ...
Tillmann Falck, Johan A. K. Suykens, Bart De Moor
CIBB
2008
14 years 11 months ago
Analysis of Kernel Based Protein Classification Strategies Using Pairwise Sequence Alignment Measures
Abstract. We evaluated methods of protein classification that use kernels built from BLAST output parameters. Protein sequences were represented as vectors of parameters (e.g. simi...
Dino Franklin, Somdutta Dhir, Sándor Pongor