Overview
- Provides a comprehensive and thorough investigation on safety concerns regarding machine learning
- Shows readers to identify vulnerabilities in machine learning models and to improve the models in the training process
- Demonstrates formal verification approaches used to identify vulnerabilities in machine learning models
Part of the book series: Artificial Intelligence: Foundations, Theory, and Algorithms (AIFTA)
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Table of contents (17 chapters)
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Safety Properties
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Safety Threats
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Safety Solutions
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Extended Safety Solutions
Keywords
About this book
The book aims to improve readers’ awareness of the potential safety issues regarding machine learning models. In addition, it includes up-to-date techniques for dealing with these issues, equipping readers with not only technical knowledge but also hands-on practical skills.
Authors and Affiliations
About the authors
Wenjie Ruan is a Senior Lecturer of Data Science at the University of Exeter, UK. His research interests lie in the adversarial robustness of deep neural networks, and in machine learning and its applications in safety-critical systems, including health data analytics and human-centered computing. His series of research works on Device-free Human Localization and Activity Recognition for Supporting the Independent Living of the Elderly garnered him a Doctoral Thesis Excellence Award from the University of Adelaide, Best Research Poster Award at the 9th ACM International Workshop on IoT and Cloud Computing, and Best Student Paper Award at the 14th International Conference on Advanced Data Mining and Applications. He was also the recipient of a prestigious DECRA fellowship from the Australian Research Council. Dr. Ruan has published more than 40 papers in international conference proceedings such as AAAI, IJCAI, SIGIR, WWW, ICDM, UbiComp, CIKM, and ASE. Dr. Ruan has served as a senior PC, PC member or invited reviewer for over 10 international conferences, including IJCAI, AAAI, ICML, NeurIPS, CVPR, ICCV, AAMAS, ECML-PKDD, etc. He is the Director of the Exeter Trustworthy AI Lab at the University of Exeter.
Bibliographic Information
Book Title: Machine Learning Safety
Authors: Xiaowei Huang, Gaojie Jin, Wenjie Ruan
Series Title: Artificial Intelligence: Foundations, Theory, and Algorithms
DOI: https://doi.org/10.1007/978-981-19-6814-3
Publisher: Springer Singapore
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023
Hardcover ISBN: 978-981-19-6813-6Published: 29 April 2023
Softcover ISBN: 978-981-19-6816-7Due: 30 May 2023
eBook ISBN: 978-981-19-6814-3Published: 28 April 2023
Series ISSN: 2365-3051
Series E-ISSN: 2365-306X
Edition Number: 1
Number of Pages: XVII, 321
Number of Illustrations: 1 b/w illustrations
Topics: Machine Learning, Systems and Data Security, Artificial Intelligence