Gnecco, Giorgio and Sanguineti, Marcello Information Complexity of Functional Optimization Problems and Their Approximation Schemes. Mathematics in Engineering, Science and Aerospace (MESA), 1 (3). pp. 303-317. ISSN 2041-3165 (2010)
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Abstract
Functional optimization is investigated using tools from information-based complexity. In such optimization problems, a functional has to be minimized with respect to admissible solutions belonging to an infinite-dimensional space of functions. This context models tasks arising in optimal control, systems identification, machine learning, time-series analysis, etc. The solution via variable-basis approximation schemes, which provide a sequence of nonlinear programming problems approximating the original functional one, is considered. Also for such problems, the information complexity is estimated.
| Item Type: | Article |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Research Area: | Computer Science and Applications |
| Depositing User: | Giorgio Gnecco |
| Date Deposited: | 17 Sep 2013 13:10 |
| Last Modified: | 17 Sep 2013 13:10 |
| URI: | http://eprints.imtlucca.it/id/eprint/1768 |
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Information complexity of functional optimization problems and their approximation schemes. (deposited 12 Sep 2013 13:26)
- Information Complexity of Functional Optimization Problems and Their Approximation Schemes. (deposited 17 Sep 2013 13:10) [Currently Displayed]
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