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We consider a confidence parametrization of binary information sources in terms of appropriate likelihood ratios. This parametrization is used for Bayesian belief updates and for the equivalent comparison of binary experiments. In contrast to the standard ...
The last decade has seen max-stable processes emerge as a common tool for the statistical modeling of spatial extremes However, their application is complicated due to the unavailability of the multivariate density function and so likehhood-based methods r ...
We have studied a camera with a very large number of binary pixels referred to as the gigavision camera or the gigapixel digital film camera. Potential advantages of this new camera design include improved dynamic range, thanks to its logarithmic sensor re ...
In this paper we present a novel approach for estimating feature-space maximum likelihood linear regression (fMLLR) transforms for full-covariance Gaussian models by directly maximizing the likelihood function by repeated line search in the direction of th ...
Consider the problem of signal detection via multiple distributed noisy sensors. We study a linear decision fusion rule of [Z. Quan, S. Cui, and A. H. Sayed, ¿Optimal Linear Cooperation for Spectrum Sensing in Cognitive Radio Networks,¿ IEEE J. Sel. Topics ...
In this paper an algorithm for nonlinear explicit model predictive control is introduced based on multiresolution function approximation that returns a low complexity approximate receding horizon control law built on a hierarchy of second order interpolets ...
Over binary input channels, uniform distribution is a universal prior, in the sense that it allows to maximize the worst case mutual information over all binary input channels, ensuring at least 94.2% of the capacity. In this paper, we address a similar qu ...
Facial expression recognition by human observers is affected by subjective components. Indeed there is no ground truth. We have developed Discrete Choice Models (DCM) to capture the human perception of facial expressions. In a first step, the static case i ...
This paper establishes that every random utility discrete choice model (RUM) has a representation that can be characterized by a choice-probability generating function (CPGF) with specific properties, and that every function with these specific properties ...
This paper introduces a general framework that evaluates a numerical Bayesian multiresponse calibration approach based on a Gibbs within Metropolis searching algorithm and a statistical likelihood function. The methodology has been applied with two version ...