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Bayesian learning of joint distributions of objects
Bayesian learning joint distributions objects
2013/4/27
There is increasing interest in broad application areas in defining flexible joint models for data having a variety of measurement scales, while also allowing data of complex types, such as functions,...
Detection of objects in noisy images based on percolation theory
signal detection image re-construction percolation noisy image unknown noise
2011/3/24
We propose a novel statistical method for detection of objects in noisy images. The method uses results from percolation and random graph theories. We present an algorithm that allows to detect object...
Robust nonparametric detection of objects in noisy images
Image analysis signal detection image recon-struction percolation noisy image nonparametric noise robust testing nite sample performance
2011/3/24
We propose a novel statistical hypothesis testing method for detection of objects in noisy images. The method uses results from percolation theory and random graph theory. We present an algorithm that...
Detection of objects in noisy images and site percolation on square lattices
Image analysis signal detection image recon-struction percolation noisy image
2011/3/24
We propose a novel probabilistic method for detection of objects in noisy images. The method uses results from percolation and random graph theories. We present an algorithm that allows to detect obje...
On dimension folding of matrix- or array-valued statistical objects
Directional regression electroencephalography Kronecker en-velope sliced inverse regression sliced average variance estimate
2010/3/11
We consider dimension reduction for regression or classification
in which the predictors are matrix- or array-valued. This type of pre-
dictor arises when measurements are obtained for each combinat...