In this paper we examine the problem of estimating the parameters of a multinomial distribution over a large number of discreteoutcomes,most of which do not appearin the training ...
This paper proposes a Bayesian approach for estimation of instrument parameter in convex image deconvolution. The parameters of the instrument response (PSF) are jointly estimated...
Bayesian network classifiers have been widely used for classification problems. Given a fixed Bayesian network structure, parameters learning can take two different approaches: ge...
Jiang Su, Harry Zhang, Charles X. Ling, Stan Matwi...
Background: Current approaches to parameter estimation are often inappropriate or inconvenient for the modelling of complex biological systems. For systems described by nonlinear ...
This paper presents a computational approach for the frequency-domain identification of multivariable, discrete-time transfer function models based on a cost function minimization...