Variational Bayesian Expectation-Maximization (VBEM), an approximate inference method for probabilistic models based on factorizing over latent variables and model parameters, has ...
This paper proposes a Bayesian algorithm to estimate the parameters of a smooth transition regression model. With in this model, time series are divided into segments and a linear...
We propose a Bayesian framework for representing and recognizing local image motion in terms of two basic models: translational motion and motion boundaries. Motion boundaries are ...
Predicting grid performance is a complex task because heterogeneous resource nodes are involved in a distributed environment. Long execution workload on a grid is even harder to pr...
Consider the minimum mean-square error (MMSE) of estimating an arbitrary random variable from its observation contaminated by Gaussian noise. The MMSE can be regarded as a function...