publication . Preprint . Article . 2016

Optimization via Separated Representations and the Canonical Tensor Decomposition

Matthew Reynolds; Gregory Beylkin; Alireza Doostan;
Open Access English
  • Published: 18 May 2016
Abstract
Comment: 13 pages, 4 figures
Persistent Identifiers
Subjects
ACM Computing Classification System: ComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONMathematicsofComputing_NUMERICALANALYSIS
free text keywords: Mathematics - Numerical Analysis, Mathematics - Optimization and Control, Physics and Astronomy (miscellaneous), Computer Science Applications, Tensor contraction, Combinatorics, Pure mathematics, Computational complexity theory, Tensor, Global optimization, Maxima, Tensor density, Mathematics, Absolute value, Rate of convergence
Related Organizations
Funded by
NSF| CAREER: Fast Surrogate Modeling for Design under Uncertainty of Complex Engineering Systems
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 1454601
  • Funding stream: Directorate for Engineering | Division of Civil, Mechanical & Manufacturing Innovation
,
NSF| A Model Reduction Approach to Stochastic PDEs: Forward Uncertainty Propagation and Stochastic Homogenization
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 1228359
  • Funding stream: Directorate for Mathematical & Physical Sciences | Division of Mathematical Sciences
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