LEADER 03802nam 22007455 450 001 9910484843703321 005 20230922181201.0 010 $a1-280-85333-6 010 $a9786610853335 010 $a3-540-48503-1 024 7 $a10.1007/978-3-540-48503-2 035 $a(CKB)1000000000282753 035 $a(EBL)3036603 035 $a(SSID)ssj0000128136 035 $a(PQKBManifestationID)11936944 035 $a(PQKBTitleCode)TC0000128136 035 $a(PQKBWorkID)10062938 035 $a(PQKB)10234987 035 $a(DE-He213)978-3-540-48503-2 035 $a(MiAaPQ)EBC3036603 035 $a(MiAaPQ)EBC6690282 035 $a(Au-PeEL)EBL6690282 035 $a(PPN)123726336 035 $a(EXLCZ)991000000000282753 100 $a20100301d2007 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aConcentration Inequalities and Model Selection $eEcole d'Eté de Probabilités de Saint-Flour XXXIII - 2003 /$fby Pascal Massart ; edited by Jean Picard 205 $a1st ed. 2007. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2007. 215 $a1 online resource (345 p.) 225 1 $aÉcole d'Été de Probabilités de Saint-Flour,$x0721-5363 ;$v1896 300 $aDescription based upon print version of record. 311 $a3-540-48497-3 320 $aIncludes bibliographical references (p. [319]-324) and index. 327 $aExponential and Information Inequalities -- Gaussian Processes -- Gaussian Model Selection -- Concentration Inequalities -- Maximal Inequalities -- Density Estimation via Model Selection -- Statistical Learning. 330 $aSince the impressive works of Talagrand, concentration inequalities have been recognized as fundamental tools in several domains such as geometry of Banach spaces or random combinatorics. They also turn out to be essential tools to develop a non-asymptotic theory in statistics, exactly as the central limit theorem and large deviations are known to play a central part in the asymptotic theory. An overview of a non-asymptotic theory for model selection is given here and some selected applications to variable selection, change points detection and statistical learning are discussed. This volume reflects the content of the course given by P. Massart in St. Flour in 2003. It is mostly self-contained and accessible to graduate students. 410 0$aÉcole d'Été de Probabilités de Saint-Flour,$x0721-5363 ;$v1896 606 $aProbabilities 606 $aStatistics  606 $aInformation theory 606 $aProbability Theory and Stochastic Processes$3https://scigraph.springernature.com/ontologies/product-market-codes/M27004 606 $aStatistical Theory and Methods$3https://scigraph.springernature.com/ontologies/product-market-codes/S11001 606 $aInformation and Communication, Circuits$3https://scigraph.springernature.com/ontologies/product-market-codes/M13038 615 0$aProbabilities. 615 0$aStatistics . 615 0$aInformation theory. 615 14$aProbability Theory and Stochastic Processes. 615 24$aStatistical Theory and Methods. 615 24$aInformation and Communication, Circuits. 676 $a511/.8 686 $a31.70$2bcl 700 $aMassart$b Pascal$4aut$4http://id.loc.gov/vocabulary/relators/aut$0472501 702 $aPicard$b Jean$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aE?cole d'e?te? de probabilite?s de Saint-Flour$d(33th :$f2003 :$eSaint-Flour, France) 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484843703321 996 $aConcentration inequalities and model selection$9230562 997 $aUNINA