LEADER 01504nam0 2200349 i 450 
001 SUN0126744
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010   $d0.00
017 70$2N$a978-3-030-24494-1
100   $a20200214d2019       |0engc50      ba
101   $aeng
102   $aCH
105   $a||||    |||||
200 1 $a*Bayesian Optimization and Data Science$fFrancesco Archetti, Antonio Candelieri
205   $aCham : Springer, 2019
210   $axiii$d126 p.$cill. ; 24 cm
215   $aPubblicazione in formato elettronico
410  1$1001SUN0102834$12001 $a*SpringerBriefs in optimization$1210  $aBerlin$cSpringer$d2012-.
606   $a68Txx$xArtificial intelligence [MSC 2020]$2MF$3SUNC021266
606   $a62-XX$xStatistics [MSC 2020]$2MF$3SUNC022998
606   $a62F15$xBayesian inference [MSC 2020]$2MF$3SUNC024528
606   $a62H30$xClassification and discrimination; cluster analysis (statistical aspects) [MSC 2020]$2MF$3SUNC028931
620   $aCH$dCham$3SUNL001889
700  1$aArchetti$b, Francesco$3SUNV098144$060966
701  1$aCandelieri$b, Antonio$3SUNV098145$0781001
712   $aSpringer$3SUNV000178$4650
801   $aIT$bSOL$c20210503$gRICA
856 4 $uhttp://doi.org/10.1007/978-3-030-24494-1
912   $aSUN0126744
950   $aUFFICIO DI BIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$d08CONS      e-book                  1520        $e08eMF1520              20200214            
996   $aBayesian Optimization and Data Science$91668171
997   $aUNICAMPANIA