Ufuk Topcu
Parameter estimation with expected and residual-at-risk criteria
In the proceedings of the Conference on Decision and Control, pp. 666-671, 2008 (G. Calafiore and L. El Ghaoui).
@INPROCEEDINGS{4738597,
title={Parameter estimation with expected and residual-at-risk criteria},
author={Calafiore, G. and Topcu, U. and El Ghaoui, L.},
booktitle={Decision and Control, 2008. CDC 2008. 47th IEEE Conference on},
year={2008},
month={Dec.},
volume={},
number={},
pages={666-671},
abstract={We study a class of uncertain linear estimation problems in which the data are affected by random uncertainty. In this setting, we consider two estimation criteria, one based on minimization of the expected 
or 
norm residual and one based on minimization of the level within which the or norm residual is guaranteed to lie with an a-priori fixed probability (residual at risk). The random uncertainty affecting the data is characterized by means of its first two statistical moments, and the above criteria are intended in a worst-case probabilistic sense, that is worst-case expectations and probabilities over all possible distribution having the specified moments are considered. The ensuing estimation problems can be solved efficiently via convex programming, yielding exact solutions in the norm case and upper-bounds on the optimal solutions in the case.},
keywords={convex programming, minimisation, parameter estimation, random processesa-priori fixed probability, convex programming, linear estimation problems, parameter estimation, random uncertainty, residual-at-risk criteria},
doi={10.1109/CDC.2008.4738597},
ISSN={0191-2216},
}