WorldCat Linked Data Explorer

Turtle N-Triple JSON-LD RDF/XML HTML Contact Us Home

http://worldcat.org/entity/work/id/33076903

New upper bounds for maximum-entropy sampling

Abstract: "We develop and experiment with new upper bounds for the constrained maximum-entropy sampling problem. Our partition bounds are based on Fischer's inequality. Further new upper bounds combine the use of Fischer's inequality with previously developed bounds. We demonstrate this in detail by using the partitioning idea to strengthen the spectral bounds of Ko, Lee and Queyranne and of Lee. Computational evidence suggests that these bounds may be useful in solving problems to optimality in a branch-and-bound framework."

Open All Close All

type

about

author

contributor

creator

description

http://schema.org/description

  • "Abstract: "We develop and experiment with new upper bounds for the constrained maximum-entropy sampling problem. Our partition bounds are based on Fischer's inequality. Further new upper bounds combine the use of Fischer's inequality with previously developed bounds. We demonstrate this in detail by using the partitioning idea to strengthen the spectral bounds of Ko, Lee and Queyranne and of Lee. Computational evidence suggests that these bounds may be useful in solving problems to optimality in a branch-and-bound framework.""@en

name

http://schema.org/name

  • "New upper bounds for maximum-entropy sampling"
  • "New upper bounds for maximum-entropy sampling"@en

workExample