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JAT
2010
51views more  JAT 2010»
15 years 1 months ago
Optimal adaptive computations in the Jaffard algebra and localized frames
We study the efficient numerical solution of infinite matrix equations Au = f for a matrix A in the Jaffard algebra. These matrices appear naturally via frame discretizations in m...
Stephan Dahlke, Massimo Fornasier, Karlheinz Gr&ou...
ICASSP
2011
IEEE
14 years 10 months ago
Comparative threshold performance study for conditional and unconditional direction-of-arrival estimation
Comparative analysis of the threshold SNR and/or sample support values where genuine maximum likelihood DOA estimation starts to produce “outliers” is conducted for unconditio...
Yuri I. Abramovich, Ben A. Johnson
CVPR
2005
IEEE
16 years 8 months ago
Nonparametric Subspace Analysis for Face Recognition
Linear discriminant analysis (LDA) is a popular face recognition technique. However, an inherent problem with this technique stems from the parametric nature of the scatter matrix...
Zhifeng Li, Wei Liu, Dahua Lin, Xiaoou Tang
177
Voted
ICCV
2001
IEEE
16 years 8 months ago
Robust Principal Component Analysis for Computer Vision
Principal Component Analysis (PCA) has been widely used for the representation of shape, appearance, and motion. One drawback of typical PCA methods is that they are least squares...
Fernando De la Torre, Michael J. Black
166
Voted
ICDM
2009
IEEE
120views Data Mining» more  ICDM 2009»
16 years 1 months ago
Least Square Incremental Linear Discriminant Analysis
Abstract—Linear discriminant analysis (LDA) is a wellknown dimension reduction approach, which projects highdimensional data into a low-dimensional space with the best separation...
Li-Ping Liu, Yuan Jiang, Zhi-Hua Zhou