β Scribed by Gilles Barthe
No coin nor oath required. For personal study only.
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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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 app
The computational foundations of Artificial Intelligence (AI) are supported by two comer stones: logics and Machine Leaming. Computationallogic has found its realization in a number of frameworks for logic-based approaches to knowledge representation and automated reasoning, such as Logic ProgramΒ m
Probabilistic Programming discusses a high-level language known as probabilistic programming.<br><br>This book consists of three chapters. Chapter I deals with βwait-and-seeΒ problems that require waiting until an observation is made on the random elements, while Chapter II contains the analysis of