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A comparison of general-purpose optimization algorithms for finding optimal approximate experimental designs.

Ricardo García-RódenasJosé Carlos García-GarcíaJesús López-FidalgoJose Angel Martin-BaosWeng Kee Wong
Published in: Comput. Stat. Data Anal. (2020)
Keyphrases
  • finding optimal
  • general purpose
  • optimization problems
  • learning algorithm
  • experimental designs
  • machine learning
  • multi agent
  • graph cuts
  • monte carlo