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TSP
2008
103views more  TSP 2008»
13 years 10 months ago
Bounds for Estimation of Covariance Matrices From Heterogeneous Samples
Abstract--This correspondence derives lower bounds on the meansquare error (MSE) for the estimation of a covariance matrix , using samples k = 1; . . . ; K, whose covariance matric...
Olivier Besson, Stéphanie Bidon, Jean-Yves ...
TSP
2008
113views more  TSP 2008»
13 years 10 months ago
Covariance Matrix Estimation With Heterogeneous Samples
We consider the problem of estimating the covariance matrix of an observation vector, using heterogeneous training samples, i.e., samples whose covariance matrices are not exactly ...
Olivier Besson, Stéphanie Bidon, Jean-Yves ...
AVBPA
2001
Springer
145views Biometrics» more  AVBPA 2001»
14 years 3 months ago
Using Mixture Covariance Matrices to Improve Face and Facial Expression Recognitions
In several pattern recognition problems, particularly in image recognition ones, there are often a large number of features available, but the number of training samples for each p...
Carlos E. Thomaz, Duncan Fyfe Gillies, Raul Queiro...
CSDA
2010
157views more  CSDA 2010»
13 years 11 months ago
Robust estimation of constrained covariance matrices for confirmatory factor analysis
Confirmatory factor analysis (CFA) is a data anylsis procedure that is widely used in social and behavioral sciences in general and other applied sciences that deal with large qua...
E. Dupuis Lozeron, M. P. Victoria-Feser
ICASSP
2009
IEEE
14 years 5 months ago
Shrinkage estimation of high dimensional covariance matrices
We address covariance estimation under mean-squared loss in the Gaussian setting. Specifically, we consider shrinkage methods which are suitable for high dimensional problems wit...
Yilun Chen, Ami Wiesel, Alfred O. Hero