Machine learning safety / Xiaowei Huang, Gaojie Jin, Wenjie Ruan.
2023
Q325.5
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Can lend chapters, not whole ebooks
Details
Title
Machine learning safety / Xiaowei Huang, Gaojie Jin, Wenjie Ruan.
Author
Huang, Xiaowei, author.
ISBN
9789811968143 (electronic bk.)
9811968144 (electronic bk.)
9811968136
9789811968136
9811968144 (electronic bk.)
9811968136
9789811968136
Published
Singapore : Springer, 2023.
Language
English
Description
1 online resource (1 volume)
Item Number
10.1007/978-981-19-6814-3 doi
Call Number
Q325.5
Dewey Decimal Classification
006.3/1
Summary
Machine learning algorithms allow computers to learn without being explicitly programmed. Their application is now spreading to highly sophisticated tasks across multiple domains, such as medical diagnostics or fully autonomous vehicles. While this development holds great potential, it also raises new safety concerns, as machine learning has many specificities that make its behaviour prediction and assessment very different from that for explicitly programmed software systems. This book addresses the main safety concerns with regard to machine learning, including its susceptibility to environmental noise and adversarial attacks. Such vulnerabilities have become a major roadblock to the deployment of machine learning in safety-critical applications. The book presents up-to-date techniques for adversarial attacks, which are used to assess the vulnerabilities of machine learning models; formal verification, which is used to determine if a trained machine learning model is free of vulnerabilities; and adversarial training, which is used to enhance the training process and reduce vulnerabilities. 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.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Description based on print version record.
Added Author
Jin, Gaojie, author.
Ruan, Wenjie, author.
Ruan, Wenjie, author.
Series
Artificial Intelligence: Foundations, Theory, and Algorithms Series.
Available in Other Form
MACHINE LEARNING SAFETY.
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Table of Contents
1. Introduction
2. Safety of Simple Machine Learning Models
3. Safety of Deep Learning
4. Robustness Verification of Deep Learning
5. Enhancement to Robustness and Generalization
6. Probabilistic Graph Model
A. Mathematical Foundations
B. Competitions.
2. Safety of Simple Machine Learning Models
3. Safety of Deep Learning
4. Robustness Verification of Deep Learning
5. Enhancement to Robustness and Generalization
6. Probabilistic Graph Model
A. Mathematical Foundations
B. Competitions.