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100   $a20221028d2022      uy             0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aMinimum divergence methods in statistical machine learning $efrom an information geometric viewpoint /$fShinto Eguchi and Osamu Komori
210  1$aTokyo, Japan :$cSpringer,$d[2022]
210  4$dŠ2022
215   $a1 online resource (224 pages)
300   $aIncludes index.
311 08$aPrint version: Eguchi, Shinto Minimum Divergence Methods in Statistical Machine Learning Tokyo : Springer Japan,c2022 9784431569206 
606   $aPattern recognition systems
606   $aMathematics
606   $aAprenentatge automātic$2thub
606   $aEstadística matemātica$2thub
608   $aLlibres electrōnics$2thub
615  0$aPattern recognition systems.
615  0$aMathematics.
615  7$aAprenentatge automātic
615  7$aEstadística matemātica
676   $a006.31
700   $aEguchi$b Shinto$0781822
702   $aKomori$b Osamu
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910552748103321
996   $aMinimum divergence methods in statistical machine learning$92961028
997   $aUNINA