Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
In this paper the blind deconvolution problem is formulated using the variational framework. With its use approximations of the involved probability distributions are developed re...
Javier Mateos, Rafael Molina, Aggelos K. Katsaggel...
Automatic image annotation automatically labels image content with semantic keywords. For instance, the Relevance Model estimates the joint probability of the keyword and the imag...
Xiangdong Zhou, Mei Wang, Qi Zhang, Junqi Zhang, B...
We introduce branching process models in discrete and continuous time for the exponentially increasing phase of cascading blackouts. Cumulative line trips from real blackout data ...
In this paper faults are processed and models of faults in telecommunications networks are proposed in relation to services and revenues. The probability of faults occurring is es...
Okuthe P. Kogeda, Johnson I. Agbinya, Christian W....