Bayesian estimation in nonlinear stochastic dynamical systems has been addressed for a long time. Among other solutions, Particle Filtering (PF) algorithms propagate in time a Mon...
The problem of aggregating multiple numerical criteria to form overall objective functions is of considerable importance in many disciplines. The ordered weighted averaging (OWA) a...
Assessing the level of information security in an enterprise is a serious challenge for many organizations. This paper considers the prioritization of the field of enterprise info...
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...