We present a computational framework to automatically discover high-order temporal social patterns from very noisy and sparse location data. We introduce the concept of social foo...
In this work we propose an approach to binary classification based on an extension of Bayes Point Machines. Particularly, we take into account the whole set of hypotheses that are...
In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
Techniques for computation on generalized diagrams are defined and the KM implications are explored. Descriptive Computing is presented and plan computation based on world models t...
Traditionally, software engineering processes are based on a formalist model that emphasizes strict documentation, procedural and validation standards. Although this is a poor fit...