ISCI
2008
13 years 4 months ago
2008
Multivariate Gaussian models are widely adopted in continuous Estimation of Distribution Algorithms (EDAs), and covariance matrix plays the essential role in guiding the evolution...
IJHPCA
2008
13 years 4 months ago
2008
Principal component analysis (PCA) is an effective tool for spectral decorrelation of hyperspectral imagery, and PCA-based spectral transforms have been employed successfully in co...
AUTOMATICA
2008
13 years 4 months ago
2008
: The problem of optimal sensor locations in nonparametric identification of viscoelastic materials is considered. Different criteria of the covariance matrix, connected to A- and ...
ICASSP
2010
IEEE
13 years 4 months ago
2010
IEEE
We consider bearing estimation of multiple narrow-band plane waves impinging on an array of sensors. For this problem, bearing estimation algorithms such as minimum variance disto...
NIPS
2004
13 years 5 months ago
2004
We examine the problem of approximating, in the Frobenius-norm sense, a positive, semidefinite symmetric matrix by a rank-one matrix, with an upper bound on the cardinality of its...
NIPS
2004
13 years 5 months ago
2004
Gaussian processes are usually parameterised in terms of their covariance functions. However, this makes it difficult to deal with multiple outputs, because ensuring that the cova...
NIPS
2007
13 years 5 months ago
2007
In this paper we investigate multi-task learning in the context of Gaussian Processes (GP). We propose a model that learns a shared covariance function on input-dependent features...
MVA
2007
13 years 5 months ago
2007
We propose use of an appearance manifold with embedded covariance matrix as a technique for recognizing 3D objects from images that are influenced by geometric and quality-degrade...
CSB
2005
IEEE
13 years 6 months ago
2005
IEEE
In microarray classification we are faced with a very large number of features and very few training samples. This is a challenge for classical Linear Discriminant Analysis (LDA),...
GECCO
2006
Springer
13 years 8 months ago
2006
Springer
First, the covariance matrix adaptation (CMA) with rankone update is introduced into the (1+1)-evolution strategy. An improved implementation of the 1/5-th success rule is propose...