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Information Complexity of Functional Optimization Problems and Their Approximation Schemes

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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