LEADER 02273nam  22004572  450 
001 9910585962103321
005 20201214100409.0
010   $a1-108-80574-4
010   $a1-108-77075-4
035   $a(CKB)4100000011576684
035   $a(UkCbUP)CR9781108770750
035   $a(MiAaPQ)EBC6563837
035   $a(Au-PeEL)EBL6563837
035   $a(OCoLC)1227044447
035   $a(EXLCZ)994100000011576684
100   $a20190321d2021||||  uy|            0
101 0 $aeng
135   $aur|||||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aFoundations of probabilistic programming /$fedited by Gilles Barthe, Joost-Pieter Katoen, Alexandra Silva$b[electronic resource]
210  1$aCambridge :$cCambridge University Press,$d2021.
215   $a1 online resource (xiv, 568 pages) $cdigital, PDF file(s)
300   $aTitle from publisher's bibliographic system (viewed on 20 Nov 2020).
311   $a1-108-48851-X 
330   $aWhat does a probabilistic program actually compute? How can one formally reason about such probabilistic programs? This valuable guide covers such elementary questions and more. It provides a state-of-the-art overview of the theoretical underpinnings of modern probabilistic programming and their applications in machine learning, security, and other domains, at a level suitable for graduate students and non-experts in the field. In addition, the book treats the connection between probabilistic programs and mathematical logic, security (what is the probability that software leaks confidential information?), and presents three programming languages for different applications: Excel tables, program testing, and approximate computing. This title is also available as Open Access on Cambridge Core.
606   $aComputer programming
606   $aProbabilities$xData processing
615  0$aComputer programming.
615  0$aProbabilities$xData processing.
676   $a001.642
702   $aBarthe$b Gilles$f1967-
702   $aKatoen$b Joost-Pieter
702   $aSilva$b Alexandra
801  0$bUkCbUP
801  1$bUkCbUP
906   $aBOOK
912   $a9910585962103321
996   $aFoundations of probabilistic programming$92904705
997   $aUNINA