A two-level low-rank approximation enables scalable A-optimal sensor design for passive imaging without repeated PDE solves in the online phase.
and Alexanderian, Alen and Ipsen, Ilse C
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Augmented Krylov subspaces jointly approximate quadratic forms and log-dets for faster MLE-based hyperparameter tuning in kernel-based linear system identification.
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Optimal experimental design for passive imaging source problems
A two-level low-rank approximation enables scalable A-optimal sensor design for passive imaging without repeated PDE solves in the online phase.