Robust Gaussian process-based global optimization using a fully Bayesian expected improvement criterion

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6683 LNCS, Issue , 2011, Pages 176-190

  Benassi, Romain ^a   Bect, Julien ^a   Vazquez, Emmanuel ^a  

^a SUPELEC   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYTICAL EXPRESSIONS; AVERAGE LOSS; BAYESIAN APPROACHES; BAYESIAN OPTIMIZATION ALGORITHMS; EFFICIENT GLOBAL OPTIMIZATION; EVALUATION RESULTS; EXPECTED IMPROVEMENTS; GAUSSIAN PROCESS PRIORS; GAUSSIAN PROCESSES; GAUSSIANS; NUMERICAL EXPERIMENTS; PLUG-INS; PREDICTIVE DISTRIBUTIONS; PRIOR INFORMATION; REAL-VALUED CONTINUOUS FUNCTIONS;

ALGORITHMS; BAYESIAN NETWORKS; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); GLOBAL OPTIMIZATION; OPTIMIZATION;

PARAMETER ESTIMATION;

EID: 84867871496     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-25566-3_13     Document Type: Conference Paper

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