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Machine Learning Safety / by Xiaowei Huang, Gaojie Jin, Wenjie Ruan
(Artificial Intelligence: Foundations, Theory, and Algorithms. ISSN:2365306X)

データ種別	電子ブック
版	1st ed. 2023.
出版者	(Singapore : Springer Nature Singapore : Imprint: Springer)
出版年	2023
大きさ	XVII, 321 p. 1 illus : online resource
著者標目	*Huang, Xiaowei author Jin, Gaojie author Ruan, Wenjie author SpringerLink (Online service)

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URL	巻　次	配架場所	請求記号	登録番号	コメント	刷　年	状　態	利用注記	ISBN	予約	請求メモ
URL		射水-電子	007	EB0001322	Computer Scinece R0 2005-6,2022-3				9789811968143

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一般注記	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 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 HTTP:URL=https://doi.org/10.1007/978-981-19-6814-3
件　名	LCSH:Machine learning LCSH:Data protection LCSH:Artificial intelligence FREE:Machine Learning FREE:Data and Information Security FREE:Artificial Intelligence
分　類	LCC:Q325.5-.7 DC23:006.31
書誌ID	EB00000710
ISBN	9789811968143