Federated Learning (Record no. 176596)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 05091nam a22006255i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-030-63076-8 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240423125319.0 |
| 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 | 201125s2020 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9783030630768 |
| -- | 978-3-030-63076-8 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-3-030-63076-8 |
| Source of number or code | doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | Q334-342 |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | TA347.A78 |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UYQ |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | COM004000 |
| Source | bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UYQ |
| Source | thema |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.3 |
| Edition number | 23 |
| 245 10 - TITLE STATEMENT | |
| Title | Federated Learning |
| Medium | [electronic resource] : |
| Remainder of title | Privacy and Incentive / |
| Statement of responsibility, etc | edited by Qiang Yang, Lixin Fan, Han Yu. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2020. |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2020. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | X, 286 p. 94 illus., 82 illus. in color. |
| 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 | Lecture Notes in Artificial Intelligence, |
| International Standard Serial Number | 2945-9141 ; |
| Volume number/sequential designation | 12500 |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Privacy -- Threats to Federated Learning -- Rethinking Gradients Safety in Federated Learning -- Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks -- Task-Agnostic Privacy-Preserving Representation Learning via Federated Learning -- Large-Scale Kernel Method for Vertical Federated Learning -- Towards Byzantine-resilient Federated Learning via Group-wise Robust Aggregation -- Federated Soft Gradient Boosting Machine for Streaming Data -- Dealing with Label Quality Disparity In Federated Learning -- Incentive -- FedCoin: A Peer-to-Peer Payment System for Federated Learning -- Efficient and Fair Data Valuation for Horizontal Federated Learning -- A Principled Approach to Data Valuation for Federated Learning -- A Gamified Research Tool for Incentive Mechanism Design in Federated Learning -- Budget-bounded Incentives for Federated Learning -- Collaborative Fairness in Federated Learning -- A Game-Theoretic Framework for Incentive Mechanism Design in Federated Learning -- Applications -- Federated Recommendation Systems -- Federated Learning for Open Banking -- Building ICU In-hospital Mortality Prediction Model with Federated Learning -- Privacy-preserving Stacking with Application to Cross-organizational Diabetes Prediction. . |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | This book provides a comprehensive and self-contained introduction to Federated Learning, ranging from the basic knowledge and theories to various key applications, and the privacy and incentive factors are the focus of the whole book. This book is timely needed since Federated Learning is getting popular after the release of the General Data Protection Regulation (GDPR). As Federated Learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. First, it introduces different privacy-preserving methods for protecting a Federated Learning model against different types of attacks such as Data Leakage and/or Data Poisoning. Second, the book presents incentive mechanisms which aim to encourage individuals to participate in the Federated Learning ecosystems. Last but not the least, this book also describeshow Federated Learning can be applied in industry and business to address data silo and privacy-preserving problems. The book is intended for readers from both academia and industries, who would like to learn federated learning from scratch, practice its implementation, and apply it in their own business. Readers are expected to have some basic understanding of linear algebra, calculus, and neural network. Additionally, domain knowledge in FinTech and marketing are preferred. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial intelligence. |
| 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 | Computer networks . |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Social sciences |
| General subdivision | Data processing. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Application software. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial Intelligence. |
| 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 | Computer Communication Networks. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer Application in Social and Behavioral Sciences. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer and Information Systems Applications. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Yang, Qiang. |
| Relator term | editor. |
| Relator code | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Fan, Lixin. |
| Relator term | editor. |
| Relator code | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Yu, Han. |
| Relator term | editor. |
| Relator code | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 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 | 9783030630751 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9783030630775 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| Uniform title | Lecture Notes in Artificial Intelligence, |
| -- | 2945-9141 ; |
| Volume number/sequential designation | 12500 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://doi.org/10.1007/978-3-030-63076-8">https://doi.org/10.1007/978-3-030-63076-8</a> |
| 912 ## - | |
| -- | ZDB-2-SCS |
| 912 ## - | |
| -- | ZDB-2-SXCS |
| 912 ## - | |
| -- | ZDB-2-LNC |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks-CSE-Springer |
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