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A learning algorithm for source aggregation
Author(s) -
Papayiannis Georgios I.,
Yannacopoulos Athanassios N.
Publication year - 2018
Publication title -
mathematical methods in the applied sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.719
H-Index - 65
eISSN - 1099-1476
pISSN - 0170-4214
DOI - 10.1002/mma.4086
Subject(s) - aggregate (composite) , mathematics , set (abstract data type) , space (punctuation) , scheme (mathematics) , mathematical optimization , algorithm , computer science , mathematical analysis , materials science , composite material , programming language , operating system
The problem of model aggregation from various information sources of unknown validity is addressed in terms of a variational problem in the space of probability measures. A weight allocation scheme to the various sources is proposed, which is designed to lead to the best aggregate model compatible with the available data and the set of prior measures provided by the information sources. Copyright © 2016 John Wiley & Sons, Ltd.