Decision diagrams (DDs) have made their way into Petri net (PN) tools either in the form of new tools (usually designed from scratch to use DDs) or as enhancements to existing tool...
Junaid Babar, Marco Beccuti, Susanna Donatelli, An...
Mixtures of Gaussians are among the most fundamental and widely used statistical models. Current techniques for learning such mixtures from data are local search heuristics with w...
We recapitulate regular one-shot learning from membership and equivalence queries, positive and negative finite data. We present a meta-algorithm that generalizes over as many sett...
We use graphical models to explore the question of how people learn simple causal relationships from data. The two leading psychological theories can both be seen as estimating th...
Typically the response of a multilayered perceptron (MLP) network on points which are far away from the boundary of its training data is not very reliable. When test data points ar...