CUR decomposition is a low-rank matrix decomposition that is formed using a small number of actual columns and actual rows of the data matrix. Since this decomposition is explicitly constructed using entries from the actual data set, CUR decomposition may be interpretable by practitioners; for this reason, it is sometimes preferable to the Singular Value…

You've probably heard some old guy rant about Newton's method and how it will solve all of your problems: linear, nonlinear, personal, laundry. There's more. In this talk I'll tell you about a way to accelerate plain vanilla fixed point iteration. The first theory for this stuff came from right here in SAS hall and…

In many modeling applications, the analytical structure of fundamental solutions to associated mathematical problems can be exploited to develop more efficient or robust numerical algorithms. I will present several examples of such approaches and techniques based on integral representations arising in the continuum modeling of materials. Some techniques to be discussed include asymptotic analysis, exploiting…