Machine Learning Safety (Record no. 173242)
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000 -LEADER | |
---|---|
fixed length control field | 03741nam a22005655i 4500 |
001 - CONTROL NUMBER | |
control field | 978-981-19-6814-3 |
003 - CONTROL NUMBER IDENTIFIER | |
control field | DE-He213 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20240423125019.0 |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
fixed length control field | cr nn 008mamaa |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 230428s2023 si | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9789811968143 |
-- | 978-981-19-6814-3 |
024 7# - OTHER STANDARD IDENTIFIER | |
Standard number or code | 10.1007/978-981-19-6814-3 |
Source of number or code | doi |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
Classification number | Q325.5-.7 |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | UYQM |
Source | bicssc |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | MAT029000 |
Source | bisacsh |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | UYQM |
Source | thema |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Classification number | 006.31 |
Edition number | 23 |
100 1# - MAIN ENTRY--PERSONAL NAME | |
Personal name | Huang, Xiaowei. |
Relator term | author. |
Relator code | aut |
-- | http://id.loc.gov/vocabulary/relators/aut |
245 10 - TITLE STATEMENT | |
Title | Machine Learning Safety |
Medium | [electronic resource] / |
Statement of responsibility, etc | by Xiaowei Huang, Gaojie Jin, Wenjie Ruan. |
250 ## - EDITION STATEMENT | |
Edition statement | 1st ed. 2023. |
264 #1 - | |
-- | Singapore : |
-- | Springer Nature Singapore : |
-- | Imprint: Springer, |
-- | 2023. |
300 ## - PHYSICAL DESCRIPTION | |
Extent | XVII, 321 p. 1 illus. |
Other physical details | online resource. |
336 ## - | |
-- | text |
-- | txt |
-- | rdacontent |
337 ## - | |
-- | computer |
-- | c |
-- | rdamedia |
338 ## - | |
-- | online resource |
-- | cr |
-- | rdacarrier |
347 ## - | |
-- | text file |
-- | |
-- | rda |
490 1# - SERIES STATEMENT | |
Series statement | Artificial Intelligence: Foundations, Theory, and Algorithms, |
International Standard Serial Number | 2365-306X |
505 0# - FORMATTED CONTENTS NOTE | |
Formatted contents note | 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. |
520 ## - SUMMARY, ETC. | |
Summary, etc | 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. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Machine learning. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Data protection. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Artificial intelligence. |
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Machine Learning. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Data and Information Security. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Artificial Intelligence. |
700 1# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Jin, Gaojie. |
Relator term | author. |
Relator code | aut |
-- | http://id.loc.gov/vocabulary/relators/aut |
700 1# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Ruan, Wenjie. |
Relator term | author. |
Relator code | aut |
-- | http://id.loc.gov/vocabulary/relators/aut |
710 2# - ADDED ENTRY--CORPORATE NAME | |
Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
773 0# - HOST ITEM ENTRY | |
Title | Springer Nature eBook |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
Display text | Printed edition: |
International Standard Book Number | 9789811968136 |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
Display text | Printed edition: |
International Standard Book Number | 9789811968150 |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
Display text | Printed edition: |
International Standard Book Number | 9789811968167 |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
Uniform title | Artificial Intelligence: Foundations, Theory, and Algorithms, |
-- | 2365-306X |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | <a href="https://doi.org/10.1007/978-981-19-6814-3">https://doi.org/10.1007/978-981-19-6814-3</a> |
912 ## - | |
-- | ZDB-2-SCS |
912 ## - | |
-- | ZDB-2-SXCS |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks-CSE-Springer |
No items available.