Name
Title | ||
|---|---|---|
Taylor approximation and variance reduction for PDE-constrained optimal control under uncertainty |
Abstract | ||
|---|---|---|
•A computational framework to solve PDE-constrained optimization under uncertainty.•Exploring the intrinsic dimensionality of the control objective in parameter space.•Taylor approximation based control variate for variance reduction.•Lagrangian formulation for eigenvalue problem constrained optimization. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.jcp.2019.01.047 | Journal of Computational Physics |
Keywords | Field | DocType |
PDE-constrained optimal control,Taylor approximation,Variance reduction,Scalability,Uncertainty quantification,High dimensionality | Discretization,Randomized algorithm,Effective dimension,Mathematical optimization,Optimal control,Control variates,Hessian matrix,Variance reduction,Mathematics,Taylor series | Journal |
Volume | ISSN | Citations |
385 | 0021-9991 | 1 |
PageRank | References | Authors |
0.37 | 19 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peng Chen | 1 | 57 | 6.49 |
| Umberto Villa | 2 | 30 | 6.64 |
| Omar Ghattas | 3 | 697 | 61.43 |