Recent Advances in Stochastic Approximation for Uncertainty Quantification: Analysis and Computation - Part II of II
For Part I, see MS-We-E-18

Date: August 13
Time: 10:00--12:00
Room: 209B

(Note: Click title to show the abstract.)

Archibald, Rick (Oak Ridge National Laboratory)
Webster, Clayton (Oak Ridge National Laboratory)
Zhang, Guannan (Oak Ridge National Laboratory)

Abstract: This mini-symposium focuses on the fundamental problem of how to accurately approximate solutions of both forward and inverse complex systems with random inputs. Predicting the behavior of complex phenomena relies on constructing solutions in terms of high dimensional spaces, particularly in the case when the input data are affected by large amounts of uncertainties. The resulting explosion in computational effort is a symptom of the curse of dimensionality. This mini-symposium aims at exploring recent advances in high-dimensional approximation, sparse polynomial approximation, multilevel methods, model calibration and data-driven reduced order modeling.

Multivariate Markov Nikolskii inequalities for polynomials on downward closed sets and application to polynomial approximation by discrete least squares
Migliorati, Giovanni (Pierre & Marie Curie Univ.)

A Stochastic Collocation Approach for Multi-Fidelity Model Classes
Narayan, Akil (Univ. of Massachusetts Dartmouth)
Xiu, Dongbin (Univ. of Utah)

Starting from measurements: an integrated UQ cycle with adaptive sparse grids
Pflueger, Dirk (Univ. of Stuttgart)


Code: Type-Date-Time-Room No.
Type : IL=Invited Lecture, SL=Special Lectures, MS=Minisymposia, IM=Industrial Minisymposia, CP=Contributed Papers, PP=Posters
Date: Mo=Monday, Tu=Tuesday, We=Wednesday, Th=Thursday, Fr=Friday
Time : A=8:30-9:30, B=10:00-11:00, C=11:10-12:10, BC=10:00-12:10, D=13:30-15:30, E=16:00-18:00, F=19:00-20:00, G=12:10-13:30, H=15:30-16:00
Room No.: TBA