Principal components analysis (PCA) is a well-known technique for approximating a data set represented by a matrix by a low rank matrix. Here, we extend the idea of PCA to handle arbitrary data sets…

Large systems of interacting particles are very complex but also interplay with a large set of applications, from cosmology to the biosciences. Particles can actually represent a wide range of…

Ezra's Round Table/Systems Engineering Seminar: Yrjo T. Grohn (Cornell) - Progression to Multi-Scale Models and the Application to Food System Intervention Strategies
Friday, April 12, 2013 at…