
Machine Learning Safety
Description
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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.
Reviews / Votes
"The authors are top researchers in the field. ... this book leaves a reader longing for more profound insights." (Subhankar Ray, Computing Reviews, March 29, 2024)
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Persons
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 9 th ACM International Workshop on IoT and Cloud Computing, and Best Student Paper Award at the 14 th 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.
Content
System requirements
File format: PDF
Copy protection: Watermark-DRM (Digital Rights Management)
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This eBook uses Watermark-DRM, a „soft” copy protection. This means that there are no technical restrictions to prevent illegal distribution. However, there is a personalised watermark embedded in the eBook that can be used to identify the purchaser of the eBook in the event of misuse and to provide evidence for legal purposes.
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