Many column subset selection criteria are NP-hard for small k and most lack polynomial-time approximation schemes.
Bayesian D-optimal experimental designs via column subset selection
3 Pith papers cite this work. Polarity classification is still indexing.
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A reformulation of Bayesian OED as dense matrix subset selection plus a pipelined Schur-complement greedy algorithm on hundreds of GPUs enables optimization of 175-sensor networks for billion-degree-of-freedom tsunami models with near-perfect scaling.
A systematic survey of optimal experimental design covering criteria formulations, estimation and optimization methods, and emerging sequential design policies.
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Sensor Placement for Tsunami Early Warning via Large-Scale Bayesian Optimal Experimental Design
A reformulation of Bayesian OED as dense matrix subset selection plus a pipelined Schur-complement greedy algorithm on hundreds of GPUs enables optimization of 175-sensor networks for billion-degree-of-freedom tsunami models with near-perfect scaling.