We extend the Bayesian Information Criterion (BIC), an asymptotic approximation for the marginal likelihood, to Bayesian networks with hidden variables. This approximation can be ...
Mutual information is widely used in artificial intelligence, in a descriptive way, to measure the stochastic dependence of discrete random variables. In order to address question...
Abstract. Estimating the degree of similarity between images is a challenging task as the similarity always depends on the context. Because of this context dependency, it seems qui...
— To approximate complex data, we propose new type of low-dimensional “principal object”: principal cubic complex. This complex is a generalization of linear and nonlinear pr...
Alexander N. Gorban, Neil R. Sumner, Andrei Yu. Zi...
Consideration of pairs of transition in probabilistic simulation allows power estimation for digital circuits in which inertial delays can filter glitches [5]. However, the merit ...