Transfer learning / (Record no. 9992)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03056nam a2200373 i 4500 |
| 001 - CONTROL NUMBER | |
| control field | CR9781139061773 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | UkCbUP |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240301142640.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS | |
| fixed length control field | m|||||o||d|||||||| |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr|||||||||||| |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 110418s2020||||enk o ||1 0|eng|d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781139061773 (ebook) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| Canceled/invalid ISBN | 9781107016903 (hardback) |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | UkCbUP |
| Language of cataloging | eng |
| Description conventions | rda |
| Transcribing agency | UkCbUP |
| 050 00 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | Q325.5 |
| Item number | .Y366 2020 |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.3/1 |
| Edition number | 23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Yang, Qiang, |
| Dates associated with a name | 1961- |
| Relator term | author. |
| 245 10 - TITLE STATEMENT | |
| Title | Transfer learning / |
| Statement of responsibility, etc. | Qiang Yang, Yu Zhang, Wenyuan Dai, Sinno Jialin Pan. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | Cambridge : |
| Name of producer, publisher, distributor, manufacturer | Cambridge University Press, |
| Date of production, publication, distribution, manufacture, or copyright notice | 2020. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 1 online resource (xi, 379 pages) : |
| Other physical details | digital, PDF file(s). |
| 336 ## - CONTENT TYPE | |
| Content type term | text |
| Content type code | txt |
| Source | rdacontent |
| 337 ## - MEDIA TYPE | |
| Media type term | computer |
| Media type code | c |
| Source | rdamedia |
| 338 ## - CARRIER TYPE | |
| Carrier type term | online resource |
| Carrier type code | cr |
| Source | rdacarrier |
| 500 ## - GENERAL NOTE | |
| General note | Title from publisher's bibliographic system (viewed on 29 Jan 2020). |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Instance-based transfer learning -- Feature-based transfer learning -- Model-based transfer learning -- Relation-based transfer learning -- Heterogeneous transfer learning -- Adversarial transfer learning -- Transfer learning in reinforcement learning -- Multi-task learning -- Transfer learning theory -- Transitive transfer learning -- AutoTL : learning to transfer automatically -- Few-shot learning -- Lifelong machine learning -- Privacy-preserving transfer learning -- Transfer learning in computer vision -- Transfer learning in natural language processing -- Transfer learning in dialogue systems -- Transfer learning in recommender systems -- Transfer learning in bioinformatics -- Transfer learning in activity recognition -- Transfer learning in urban computing. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Transfer learning deals with how systems can quickly adapt themselves to new situations, tasks and environments. It gives machine learning systems the ability to leverage auxiliary data and models to help solve target problems when there is only a small amount of data available. This makes such systems more reliable and robust, keeping the machine learning model faced with unforeseeable changes from deviating too much from expected performance. At an enterprise level, transfer learning allows knowledge to be reused so experience gained once can be repeatedly applied to the real world. For example, a pre-trained model that takes account of user privacy can be downloaded and adapted at the edge of a computer network. This self-contained, comprehensive reference text describes the standard algorithms and demonstrates how these are used in different transfer learning paradigms. It offers a solid grounding for newcomers as well as new insights for seasoned researchers and developers. |
| 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 | Artificial intelligence. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Zhang, Yu |
| Titles and other words associated with a name | (Professor of computer science), |
| Dates associated with a name | 1982- |
| Relator term | author. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Dai, Wenyuan, |
| Dates associated with a name | 1983- |
| Relator term | author. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Pan, Sinno Jialin, |
| Dates associated with a name | 1980- |
| Relator term | author. |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Print version: |
| International Standard Book Number | 9781107016903 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://doi.org/10.1017/9781139061773">https://doi.org/10.1017/9781139061773</a> |
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