Generalized Bradley-Terry Models for Score Estimation from Paired Comparisons
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Powerful mathematical tools have been developed for trading in stocks and bonds, but other markets that are equally important for the globalized world have to some extent been neglected. We decided to study the shipping market as an new area of development ...
We consider the problem of ranging with impulse radio (IR) ultra-wideband (UWB) radio under dense multipaths propagation environments and additive Gaussian noise. We propose a Bayesian detection algorithm where the prior distribution of the channel follows ...
We consider the problem of positioning estimation with impulse radio (IR) ultra-wideband (UWB) radio under dense multipaths and additive Gaussian noise environments. Most popular positioning algorithms first estimate certain parameters (such as time of arr ...
We show that estimation of parameters for the popular Gaussian model of speech in noise can be regularised in a Bayesian sense by use of simple prior distributions. For two example prior distributions, we show that the marginal distribution of the uncorrup ...
This paper presents a calibration framework based on the generalized likelihood uncertainty estimation (GLUE) that can be used to condition hydrological model parameter distributions in scarcely gauged river basins, where data is uncertain, intermittent or ...
In this paper, we present initial results towards boosting posterior based speech recognition systems by estimating more informative posteriors using multiple streams of features and taking into account acoustic context (e.g., as available in the whole utt ...
The thesis is a contribution to extreme-value statistics, more precisely to the estimation of clustering characteristics of extreme values. One summary measure of the tendency to form groups is the inverse average cluster size. In extreme-value context, th ...
In this work, we study a communication scheme in which nodes transmit sufficient statistics of their observations over non-orthogonal medium access channels for distributed estimation. This scheme unifies and generalizes several multiple access schemes suc ...
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In this paper, we present initial results towards boosting posterior based speech recognition systems by estimating more informative posteriors using multiple streams of features and taking into account acoustic context (e.g., as available in the whole utt ...
In time series analysis state-space models provide a wide and flexible class. The basic idea is to describe an unobservable phenomenon of interest on the basis of noisy data. The first constituent of such a model is the so-called state equation, which char ...