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Enhanced Kriging Models within a Bayesian Optimization Framework, to Handle both continuous and Categorical Inputs

Saves, P.; Bartoli, N.; Lefebre, T.; Diouane, Y.; Morlier, J.


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  <dc:creator>Saves, P.</dc:creator>
  <dc:creator>Bartoli, N.</dc:creator>
  <dc:creator>Lefebre, T.</dc:creator>
  <dc:creator>Diouane, Y.</dc:creator>
  <dc:creator>Morlier, J.</dc:creator>
  <dc:date>2021-03-05</dc:date>
  <dc:description>SIAM Conference on Computational Science and Engineering

MS130 Derivative-Free Optimization Methods for Solving Expensive Global Black-Box Problems - Part II of II</dc:description>
  <dc:identifier>https://zenodo.org/record/5743339</dc:identifier>
  <dc:identifier>10.5281/zenodo.5743339</dc:identifier>
  <dc:identifier>oai:zenodo.org:5743339</dc:identifier>
  <dc:relation>info:eu-repo/grantAgreement/EC/Horizon 2020 Framework Programme - Research and Innovation action/815122/</dc:relation>
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  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>Bayesian optimization</dc:subject>
  <dc:subject>kriging</dc:subject>
  <dc:title>Enhanced Kriging Models within a Bayesian Optimization Framework, to Handle both continuous and Categorical Inputs</dc:title>
  <dc:type>info:eu-repo/semantics/lecture</dc:type>
  <dc:type>presentation</dc:type>
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