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arXiv · 2409.09963

A global optimum-informed greedy algorithm for A-optimal experimental design

Christian Aarset
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Abstract

Optimal experimental design (OED) concerns itself with identifying ideal methods of data collection, e.g.~via sensor placement. The \emph{greedy algorithm}, that is, placing one sensor at a time, in an iteratively optimal manner, stands as an extremely robust and easily executed algorithm for this purpose. However, it is a priori unclear whether this algorithm leads to sub-optimal regimes. Taking advantage of the author's recent work on non-smooth convex optimality criteria for OED, we here present a framework for rejection of sub-optimal greedy indices, and study the numerical benefits this offers.

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Christian Aarset. 2024-09-16. A global optimum-informed greedy algorithm for A-optimal experimental design. https://doi.org/10.1007/978-3-031-87213-6_24

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