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Using continuous nonlinear relaxations to solve. constrained maximum-entropy sampling problems

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Authors and Affiliations

  1. Dept. of Management Sciences, University of Iowa, Iowa City, IA 52242 Research conducted while visiting the Center for Operations Research and Econometrics, Université catholique de Louvain, supported by a CORE Fellowship, , , , , , US

    Kurt M. Anstreicher

  2. Inst. of Mathematics – COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil Research conducted while visiting the Dept. of Management Sciences, University of Iowa, supported by a Research Fellowship from CNPq-Brasilia-Brazil, , , , , , BR

    Marcia Fampa

  3. Dept. of Mathematics, University of Kentucky, Lexington, KY 40506-0027. Supported in part by NSF grant DMI-9401424, , , , , , US

    Jon Lee

  4. Dept. of Mathematics, University of Kentucky, Lexington, KY 40506-0027. Supported in part by NSF grant DMI-9401424 and by the U.K. Center for Computational Sciences, , , , , , US

    Joy Williams

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  1. Kurt M. Anstreicher
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  2. Marcia Fampa
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  3. Jon Lee
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  4. Joy Williams
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Received January 9, 1997 / Revised version received January 26, 1998 Published online November 24, 1998

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Anstreicher, K., Fampa, M., Lee, J. et al. Using continuous nonlinear relaxations to solve. constrained maximum-entropy sampling problems. Math. Program. 85, 221–240 (1999). https://doi.org/10.1007/s101070050055

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  • DOI: https://doi.org/10.1007/s101070050055

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