It is commonly agreed that a self-adaptive software system is one that can modify itself at run-time due to changes in the system, its requirements, or the environment in which it ...
We show how variational Bayesian inference can be implemented for very large generalized linear models. Our relaxation is proven to be a convex problem for any log-concave model. ...
Naive Bayes models have been widely used for clustering and classification. However, they are seldom used for general probabilistic learning and inference (i.e., for estimating an...
Hidden Markov Models (HMM) are probabilistic graphical models for interdependent classification. In this paper we experiment with different ways of combining the components of an ...
A lot of research and work has been done in the past, to develop XML based user-interface definition languages. Also languages to describe graphics and animations were created. In...