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Approximation Schemes for Functional Optimization Problems.
- Source :
- Journal of Optimization Theory & Applications; Jan2009, Vol. 140 Issue 1, p33-54, 22p, 2 Diagrams, 3 Charts, 2 Graphs
- Publication Year :
- 2009
-
Abstract
- Approximation schemes for functional optimization problems with admissible solutions dependent on a large number d of variables are investigated. Suboptimal solutions are considered, expressed as linear combinations of n-tuples from a basis set of simple computational units with adjustable parameters. Different choices of basis sets are compared, which allow one to obtain suboptimal solutions using a number n of basis functions that does not grow “fast” with the number d of variables in the admissible decision functions for a fixed desired accuracy. In these cases, one mitigates the “curse of dimensionality,” which often makes unfeasible traditional linear approximation techniques for functional optimization problems, when admissible solutions depend on a large number d of variables. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00223239
- Volume :
- 140
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Journal of Optimization Theory & Applications
- Publication Type :
- Academic Journal
- Accession number :
- 35996809
- Full Text :
- https://doi.org/10.1007/s10957-008-9471-6