Foundations of probabilistic programming / edited by Gilles Barthe, Joost-Pieter Katoen, Alexandra Silva.
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TextPublisher: Cambridge University Press, Description: 1 online resource (xiv, 568 pages) : digital, PDF file(s)ISBN: 9781108770750 (ebook)Subject(s): Computer programming | Probabilities -- Data processingAdditional physical formats: Print version: : No titleDDC classification: 001.642 LOC classification: QA76.6 | .F69 2021Online resources: Click here to access online Summary: What 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.
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Title from publisher's bibliographic system (viewed on 20 Nov 2020).
What 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.
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