Jorge Cortés
Professor
Cymer Corporation Endowed Chair
Set-valued regression and cautious suboptimization:
from noisy data to optimality
J. Eising, J. Cortés
Proceedings of the IEEE Conference on
Decision and Control, Singapore, 2023,
pp. 5319-5324
Abstract
This paper deals with the problem of finding suboptimal values of an
unknown function on the basis of measured data corrupted by bounded
noise. As a prior, we assume that the unknown functions is
parameterized in terms of a number of basis functions. Inspired by the
informativity approach, we view the problem as the suboptimization of
the worst-case estimate of the function. The paper provides closed
form solutions and convexity results for this function, which enables
us to solve the problem. After this, an online implementation is
investigated, where we iteratively measure the function and perform a
suboptimization. This nets a procedure that is safe at each step, and
which, under mild assumptions, converges to the true optimizer.
pdf
Mechanical and Aerospace Engineering,
University of California, San Diego
9500 Gilman Dr,
La Jolla, California, 92093-0411
Ph: 1-858-822-7930
Fax: 1-858-822-3107
cortes at ucsd.edu
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jorgilliyo