AMS Colloquium 11-15-13
One of the largest issues facing the ever-growing field of large-scale computational research is how to deal with the nearly infinite number of parameters needed to exactly model a physical reality. With no efficient or cost-effective way to handle the enormous numbers of tests needed to even begin to satisfy requirements needed to model reality, it is inevitable that models will need to be parameterized. However, this causes a problem known as the “Curse of Dimensionality,” in which for every unavoidable parameter used in a model, there is an unavoidable uncertainty associated with the assumption(s) used to define said parameter. As part of his current research, Dr. Tan Bui-Thanh of the University of Texas presented on how he is working on how to deal with computational problems involving these discretization errors.
