Artificial Intelligence

Adversarial Robustness for Machine Learning

Name: Adversarial Robustness for Machine Learning
Brand: Academic Press
SKU: 9780128240205
Price: 11933.00 INR
Availability: InStock
ISBN: 9780128240205

Contributor(s): Chen, Pin-Yu Author , Hsieh, Cho-Jui Author Format: Paperback

Paperback · ISBN 9780128240205

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Key Specifications

ISBN	9780128240205
Publisher	Academic Press
Publication date	September 2022
Language	English
MRP	£84.95 GBP
Page count	298
Item weight	89 g

Adversarial Robustness for Machine Learning summarizes the recent progress on this topic and introduces popular algorithms on adversarial attack, defense and veriﬁcation. Sections cover adversarial attack, veriﬁcation and defense, mainly focusing on image classiﬁcation applications which are the standard benchmark considered in the adversarial robustness community. Other sections discuss adversarial examples beyond image classification, other threat models beyond testing time attack, and applications on adversarial robustness. For researchers, this book provides a thorough literature review that summarizes latest progress in the area, which can be a good reference for conducting future research.

In addition, the book can also be used as a textbook for graduate courses on adversarial robustness or trustworthy machine learning. While machine learning (ML) algorithms have achieved remarkable performance in many applications, recent studies have demonstrated their lack of robustness against adversarial disturbance. The lack of robustness brings security concerns in ML models for real applications such as self-driving cars, robotics controls and healthcare systems.

Adversarial Robustness for Machine Learning

Key Specifications

Chen, Pin-Yu Author

Hsieh, Cho-Jui Author

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