LEADER 02442nam0 22004813i 450 001 VAN0274859 005 20240618114112.144 017 70$2N$a9783030821715 100 $a20240412d2021 |0itac50 ba 101 $aeng 102 $aCH 105 $a|||| ||||| 200 1 $aKernel Mode Decomposition and the Programming of Kernels$fHouman Owhadi, Clint Scovel, Gene Ryan Yoo 210 $aCham$cSpringer$d2021 215 $ax, 118 p.$cill.$d24 cm 410 1$1001VAN0249506$12001 $aSurveys and Tutorials in the Applied Mathematical Sciences$1210 $aBerlin [etc.]$cSpringer$v8 606 $a68T10$xPattern recognition, speech recognition [MSC 2020]$3VANC020788$2MF 606 $a62J02$xGeneral nonlinear regression [MSC 2020]$3VANC021211$2MF 606 $a62-XX$xStatistics [MSC 2020]$3VANC022998$2MF 606 $a62G07$xDensity estimation [MSC 2020]$3VANC024543$2MF 606 $a62J12$xGeneralized linear models (logistic models) [MSC 2020]$3VANC025019$2MF 606 $a62R07$xStatistical aspects of big data and data science [MSC 2020]$3VANC026514$2MF 606 $a62H30$xClassification and discrimination; cluster analysis (statistical aspects) [MSC 2020]$3VANC028931$2MF 606 $a62G08$xNonparametric regression and quantile regression [MSC 2020]$3VANC029587$2MF 606 $a68T09$xComputational aspects of data analysis and big data [MSC 2020]$3VANC035916$2MF 610 $aAdditive models$9KW:K 610 $aEmpirical mode decomposition$9KW:K 610 $aGaussian process regression$9KW:K 610 $aKernel methods$9KW:K 610 $aTime-frequency decomposition$9KW:K 620 $aCH$dCham$3VANL001889 700 1$aOwhadi$bHouman$3VANV099002$01074716 701 1$aScovel$bClint$3VANV227307$01734773 701 1$aYoo$bGene Ryan$3VANV227308$01734774 712 $aSpringer $3VANV108073$4650 801 $aIT$bSOL$c20240621$gRICA 856 4 $uhttps://doi.org/10.1007/978-3-030-82171-5$zE-book ? Accesso al full-text attraverso riconoscimento IP di Ateneo, proxy e/o Shibboleth 899 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$1IT-CE0120$2VAN08 912 $fN 912 $aVAN0274859 950 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$d08CONS e-book 8282 $e08eMF8282 20240430 996 $aKernel Mode Decomposition and the Programming of Kernels$94153289 997 $aUNICAMPANIA