MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03423nam a22003617a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
CSPC |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20260708143535.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
260708s2023 si a b 000 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9789811968136 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
CSPC |
| Language of cataloging |
eng |
| Transcribing agency |
CSPC |
| Modifying agency |
CSPC |
| Description conventions |
rda |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
Q325.5 |
| Item number |
.H83 2023 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
006.31 |
| Item number |
H860m |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Huang, Xiaowei, |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Machine learning safety / |
| Statement of responsibility, etc. |
Xiaowei Huang, Gaojie Jin, and Wenjie Ruan. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Singapore : |
| Name of producer, publisher, distributor, manufacturer |
Springer Nature Singapore Pte Ltd., |
| Date of production, publication, distribution, manufacture, or copyright notice |
2023. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xvii, 321 pages : |
| Other physical details |
illustrations ; |
| Dimensions |
24 cm. |
| 336 ## - CONTENT TYPE |
|---|
| Source |
rdacontent |
| Content type term |
text |
| 337 ## - MEDIA TYPE |
|---|
| Source |
rdamedia |
| Media type term |
unmediated |
| 338 ## - CARRIER TYPE |
|---|
| Source |
rdacarrier |
| Carrier type term |
volume |
| 490 0# - SERIES STATEMENT |
|---|
| Series statement |
Artificial intelligence : foundations, theory, and algorithms |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references. |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Safety properties -- Machine learning basics -- Model evaluation methods -- Safety and security properties -- Practice -- Safety threats -- Decision tree -- K-nearest neighbor -- Linear regression -- Naive bayes -- Loss function and gradient descent -- Deep learning -- Safety solutions -- Verification of deep learning -- Enhancement to safety and security of deep learning -- Extended safety solutions -- Deep reinforced learning -- Testing techniques -- Reliability assessment -- Assurance of machine learning lifecycle -- Probabilistic graph models for feature robustness -- Appendix: mathematical foundations and competition -- probability theory -- Linear algebra -- Probabilistic graph models -- Competition: resilience to adversarial attack. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
"<br/>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"-- Worldcat. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Machine learning. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Data protection. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Artificial intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Machine learning |
| General subdivision |
Safety measures. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Computer security. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Jin, Gaojie, |
| Relator term |
author. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Ruan, Wenjie, |
| Relator term |
author. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Suppress in OPAC |
No |
| Koha item type |
Books |
| Classification part |
006.31 |
| Item part |
H860m |
| Call number prefix |
GRD |
| Call number suffix |
2023 |
| Edition |
23 |