Introduction to Neural Network Verification

di Aws Albarghouthi (Autore)

now publishers Inc, 2021

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.

• Autore: Aws Albarghouthi
• Editore: now publishers Inc
• Collana: Foundations and Trends (R) in Programming Languages
• Anno: 2021
• Rilegatura: Paperback / softback
• Pagine: 180 p.
• Dimensioni: 234 x 156 mm
• Peso: 262 gr.
• EAN: 9781680839104

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