On the inference of semi-coherent structures from data

Authors:
D. H. Judson;Sitadri Bagchi;Thomas Quint
Affiliations:
Administrative Records Evaluation and Linkage, Planning, Research and Evaluation Division, US Census Bureau, Suitland, MD;Department of Mathematics, University of Nevada, Reno, NV;Department of Mathematics, University of Nevada, Reno, NV
Venue:
Computers and Operations Research
Year:
2005

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Abstract

In this paper, we consider an unknown semi-coherent structure function. Our main focus is the inductive inference problem, that is, how to learn the structure function from data which partially defines the function. We develop a set of algorithms and simulate their success in learning an arbitrary 10-component function, and conclude that the algorithms are feasible.