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. 303317. ISSN 20413165 (2010)
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Abstract
Functional optimization is investigated using tools from informationbased complexity. In such optimization problems, a functional has to be minimized with respect to admissible solutions belonging to an infinitedimensional space of functions. This context models tasks arising in optimal control, systems identification, machine learning, timeseries analysis, etc. The solution via variablebasis 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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