We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. denite clause programs containing probabilistic facts with a ...
Based on a recent development in the area of error control coding, we introduce the notion of convolutional factor graphs (CFGs) as a new class of probabilistic graphical models. ...
We develop a new graphical representation for interactive partially observable Markov decision processes (I-POMDPs) that is significantly more transparent and semantically clear t...
In response to current technology scaling trends, architects are developing a new style of processor, known as spatial computers. A spatial computer is composed of hundreds or eve...
Martha Mercaldi, Steven Swanson, Andrew Petersen, ...
Model-based development promises to increase productivity by offering modeling languages tailored to a specific domain. Such modeling languages are typically defined by a metamodel...