Introduction to Neural Network Verification (Foundations and Trends(r) in Programming Languages)

Albarghouthi, Aws

ISBN 10: 1680839101 / ISBN 13: 9781680839104

Published by Now Publishers, 2021

About this Item

This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Seller Inventory # ABNR-286732

Bibliographic Details

• Title: Introduction to Neural Network Verification (Foundations and Trends(r) in Programming Languages)
• Publisher: Now Publishers
• Publication Date: 2021
• Language: English
• ISBN 10: 1680839101
• ISBN 13: 9781680839104
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Over the past decade, a number of hardware and software advances have conspired to thrust deep learning and neural networks to the forefront of computing. Deep learning has created a qualitative shift in our conception of what software is and what it can do: Every day we're seeing new applications of deep learning, from healthcare to art, and it feels like we're only scratching the surface of a universe of new possibilities. This book offers the first introduction of foundational ideas from automated verification as applied to deep neural networks and deep learning. It is divided into three parts: Part 1 defines neural networks as data-flow graphs of operators over real-valued inputs. Part 2 discusses constraint-based techniques for verification. Part 3 discusses abstraction-based techniques for verification. The book is a self-contained treatment of a topic that sits at the intersection of machine learning and formal verification. It can serve as an introduction to the field for first-year graduate students or senior undergraduates, even if they have not been exposed to deep learning or verification.