A Near-Optimal Sampling Strategy for Sparse Recovery of Polynomial Chaos
Expansions

v1v2 (latest)

A Near-Optimal Sampling Strategy for Sparse Recovery of Polynomial Chaos Expansions

25 February 2017

Negin Alemazkoor

ArXiv (abs)PDF HTML

Papers citing "A Near-Optimal Sampling Strategy for Sparse Recovery of Polynomial Chaos Expansions"

5 / 5 papers shown

Title
Multi-fidelity Machine Learning for Uncertainty Quantification and Optimization Ruda Zhang Negin Alemazkoor AI4CE 111 5 0 30 Oct 2024
On efficient algorithms for computing near-best polynomial approximations to high-dimensional, Hilbert-valued functions from limited samples Ben Adcock Simone Brugiapaglia N. Dexter S. Moraga 132 11 0 25 Mar 2022
Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark Nora Lüthen S. Marelli Bruno Sudret 169 171 0 04 Feb 2020
Sparse Polynomial Chaos Expansions via Compressed Sensing and D-optimal Design Paul Diaz Alireza Doostan Jerrad Hampton 106 102 0 29 Dec 2017
A preconditioning approach for improved estimation of sparse polynomial chaos expansions Negin Alemazkoor Hadi Meidani 88 9 0 22 Sep 2017