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...
This paper introduces a methodology to help the programmer in the transition from a set of desired global properties expressed as an equation-based model (EBM) that a Multi-Agent ...
We introduce PLC-Automata as a new class of automata which are tailored to deal with real-time properties of Programmable Logic Controllers (PLCs). These devices are often used in...
We study maximum a posteriori probability model order selection for linear regression models, assuming Gaussian distributed noise and coefficient vectors. For the same data model,...
—Synthetic magnetic resonance (MR) imaging is an approach suggested in the literature to predict MR images at different design parameter settings from at least three observed MR ...