Alternating direction method for enhancing sparsity of the representation of uncertainty

Date
11/27/2017
Location
4:30PM at UNIV 103
Speaker
Dr. Xiu Yang, Pacific Northwest National Lab
Title
Alternating direction method for enhancing sparsity of the representation of uncertainty
Host
Description

Compressive sensing has become a powerful tool for uncertainty quantification when only limited data is available. We provide a general framework using alternating direction method to enhance the sparsity of the representation of uncertainty in the form of generalized polynomial chaos expansion. This method identifies new sets of random variables through iterative rotations such that the new representation of the uncertainty using these variables is sparser. Consequently, we increase both the efficiency and accuracy of the compressive sensing-based uncertainty quantification method. We demonstrate the effectiveness of this method with applications in analyzing uncertainties in high-dimensional complex systems.