eprintid: 1703
rev_number: 6
eprint_status: archive
userid: 46
dir: disk0/00/00/17/03
datestamp: 2013-09-12 13:26:20
lastmod: 2013-09-16 12:03:00
status_changed: 2013-09-12 13:26:20
type: article
metadata_visibility: no_search
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)