MARC details
| 000 -LIDER |
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| fixed length control field |
04643nam a22006015i 4500 |
| 001 - CONTROL NUMBER |
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| control field |
978-981-97-1025-6 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20250516160025.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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| fixed length control field |
cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
240422s2024 si | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9789819710256 |
| -- |
978-981-97-1025-6 |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
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| 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 |
Li, Jingjing. |
| Relator term |
author. |
| Relator code |
aut |
| -- |
http://id.loc.gov/vocabulary/relators/aut |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Unsupervised Domain Adaptation |
| Medium |
[electronic resource] : |
| Remainder of title |
Recent Advances and Future Perspectives / |
| Statement of responsibility, etc. |
by Jingjing Li, Lei Zhu, Zhekai Du. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
1st ed. 2024. |
| 264 #1 - |
|---|
| -- |
Singapore : |
| -- |
Springer Nature Singapore : |
| -- |
Imprint: Springer, |
| -- |
2024. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
XVI, 223 p. 78 illus., 44 illus. in color. |
| Other physical details |
online resource. |
| 336 ## - |
|---|
| -- |
text |
| -- |
txt |
| -- |
rdacontent |
| 337 ## - |
|---|
| -- |
computer |
| -- |
c |
| -- |
rdamedia |
| 338 ## - |
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| -- |
online resource |
| -- |
cr |
| -- |
rdacarrier |
| 347 ## - |
|---|
| -- |
text file |
| -- |
PDF |
| -- |
rda |
| 490 1# - SERIES STATEMENT |
|---|
| Series statement |
Machine Learning: Foundations, Methodologies, and Applications, |
| International Standard Serial Number |
2730-9916 |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Chapter 1. Introduction to Domain Adaptation -- Chapter 2. Unsupervised Domain Adaptation Techniques -- Chapter 3. Criterion Optimization-Based Unsupervised Domain -- Chapter 4. Bi-Classifier Adversarial Learning-Based Unsupervised Domain -- Chapter 5. Source-Free Unsupervised Domain Adaptation -- Chapter 6. Active Learning for Unsupervised Domain Adaptation -- Chapter 7. Continual Test-Time Unsupervised Domain Adaptation -- Chapter 8. Applications -- Chapter 9. Research Frontier. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Unsupervised domain adaptation (UDA) is a challenging problem in machine learning where the model is trained on a source domain with labeled data and tested on a target domain with unlabeled data. In recent years, UDA has received significant attention from the research community due to its applicability in various real-world scenarios. This book provides a comprehensive review of state-of-the-art UDA methods and explores new variants of UDA that have the potential to advance the field. The book begins with a clear introduction to the UDA problem and is mainly organized into four technical sections, each focused on a specific piece of UDA research. The first section covers criterion optimization-based UDA, which aims to learn domain-invariant representations by minimizing the discrepancy between source and target domains. The second section discusses bi-classifier adversarial learning-based UDA, which creatively leverages adversarial learning by conducting a minimax game between the feature extractor and two task classifiers. The third section introduces source-free UDA, a novel UDA setting that does not require any raw data from the source domain. The fourth section presents active learning for UDA, which combines domain adaptation and active learning to reduce the amount of labeled data needed for adaptation. This book is suitable for researchers, graduate students, and practitioners who are interested in UDA and its applications in various fields, primarily in computer vision. The chapters are authored by leading experts in the field and provide a comprehensive and in-depth analysis of the current UDA methods and new directions for future research. With its broad coverage and cutting-edge research, this book is a valuable resource for anyone looking to advance their knowledge of UDA. |
| 541 ## - IMMEDIATE SOURCE OF ACQUISITION NOTE |
|---|
| Owner |
UABC ; |
| Method of acquisition |
Perpetuidad |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Término temático o nombre geográfico como elemento de entrada |
Machine learning. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Término temático o nombre geográfico como elemento de entrada |
Artificial intelligence |
| Subdivisión general |
Data processing. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Término temático o nombre geográfico como elemento de entrada |
Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Término temático o nombre geográfico como elemento de entrada |
Distribution (Probability theory). |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Término temático o nombre geográfico como elemento de entrada |
Machine Learning. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Término temático o nombre geográfico como elemento de entrada |
Data Science. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Término temático o nombre geográfico como elemento de entrada |
Data Mining and Knowledge Discovery. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Término temático o nombre geográfico como elemento de entrada |
Distribution Theory. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Zhu, Lei. |
| Relator term |
author. |
| Relator code |
aut |
| -- |
http://id.loc.gov/vocabulary/relators/aut |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Du, Zhekai. |
| 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 |
|---|
| Relationship information |
Printed edition: |
| International Standard Book Number |
9789819710249 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Printed edition: |
| International Standard Book Number |
9789819710263 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Printed edition: |
| International Standard Book Number |
9789819710270 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Machine Learning: Foundations, Methodologies, and Applications, |
| -- |
2730-9916 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Public note |
Libro electrónico |
| Uniform Resource Identifier |
http://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-981-97-1025-6 |
| 912 ## - |
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| -- |
ZDB-2-SCS |
| 912 ## - |
|---|
| -- |
ZDB-2-SXCS |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
Libro Electrónico |
