Many scholars believe that electronic rulemaking has great but largely untapped potential to expand the public's democratic input and improve federal agency regulatory rules....
Peter Muhlberger, Nick Webb, Jennifer Stromer-Gall...
Abstract. We discuss causal structure learning based on linear structural equation models. Conventional learning methods most often assume Gaussianity and create many indistinguish...
We first present a method, called Two-Phase Pareto Local Search, to find a good approximation of the efficient set of the biobjective traveling salesman problem. In the first p...
Single and multi-step time-series predictors were evolved for forecasting minimum bidding prices in a simulated supply chain management scenario. Evolved programs were allowed to ...
Alexandros Agapitos, Matthew Dyson, Jenya Kovalchu...
This paper addresses the image registration problem applying genetic algorithms. The image registration’s objective is the definition of a mapping that best match two set of poi...