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Maximum entropy and feasibility methods for convex and non-convex inverse problems.

Borwein, Jonathan M. (2012) Maximum entropy and feasibility methods for convex and non-convex inverse problems. Optimization, 61 . pp. 1-33.

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    Abstract

    We discuss informally two approaches to solving convex and nonconvex feasibility problems – via entropy optimization and via algebraic iterative methods. We shall highlight the advantages and disadvantages of each and give various related applications and limiting examples. While some of the results are very classical, they are not as well-known to practitioners as they should be. A key role is played by the Fenchel conjugate.

    Item Type: Article
    Additional Information: Invited. DOI: 10.1080/02331934.2011.632502.
    Subjects: UNSPECIFIED
    Faculty: UNSPECIFIED
    Depositing User: Dr David Allingham
    Date Deposited: 29 Oct 2012 17:33
    Last Modified: 03 Jan 2015 21:26
    URI: https://docserver.carma.newcastle.edu.au/id/eprint/1439

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