The paper extends some of the most recently obtained results on the computational universality of speci c variants of H systems (e.g. with regular sets of rules) and proves that we...
A goal of statistical language modeling is to learn the joint probability function of sequences of words in a language. This is intrinsically difficult because of the curse of dim...
Learning of a smooth but nonparametric probability density can be regularized using methods of Quantum Field Theory. We implement a field theoretic prior numerically, test its eff...
: Framelets and implementation cases are new concepts to manage the complexity of product line development. Framelets are "small product lines" that address, as self-stan...
Input modeling that involves fitting standard univariate parametric probability distributions is typically performed using an input modeling package. These packages typically fit ...