eprintid: 1768 rev_number: 4 eprint_status: archive userid: 46 dir: disk0/00/00/17/68 datestamp: 2013-09-17 13:10:16 lastmod: 2013-09-17 13:10:16 status_changed: 2013-09-17 13:10:16 type: article succeeds: 1703 metadata_visibility: show creators_name: Gnecco, Giorgio creators_name: Sanguineti, Marcello creators_id: giorgio.gnecco@imtlucca.it creators_id: title: Information Complexity of Functional Optimization Problems and Their Approximation Schemes ispublished: pub subjects: QA75 divisions: CSA full_text_status: none 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. date: 2010 date_type: published publication: Mathematics in Engineering, Science and Aerospace (MESA) volume: 1 number: 3 pagerange: 303-317 refereed: TRUE issn: 2041-3165 official_url: http://nonlinearstudies.com/index.php/mesa/article/view/403 citation: 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)