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A01=Jindong Wang
A01=Yiqiang Chen
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Author_Jindong Wang
Author_Yiqiang Chen
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Introduction to Transfer Learning: Algorithms and Practice

English

By (author): Jindong Wang Yiqiang Chen

Transfer learning is one of the most important technologies in the era of artificial intelligence and deep learning. It seeks to leverage existing knowledge by transferring it to another, new domain. Over the years, a number of relevant topics have attracted the interest of the research and application community: transfer learning, pre-training and fine-tuning, domain adaptation, domain generalization, and meta-learning.

 This book offers a comprehensive tutorial on an overview of transfer learning, introducing new researchers in this area to both classic and more recent algorithms. Most importantly, it takes a students perspective to introduce all the concepts, theories, algorithms, and applications, allowing readers to quickly and easily enter this area. Accompanying the book, detailed code implementations are provided to better illustrate the core ideas of several important algorithms, presenting good examples for practice.


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A01=Jindong WangA01=Yiqiang ChenAge Group_UncategorizedAuthor_Jindong WangAuthor_Yiqiang Chenautomatic-updateCategory1=Non-FictionCategory=UYACategory=UYQLCategory=UYQMCategory=UYQVCOP=SingaporeDelivery_Pre-orderLanguage_EnglishPA=Not yet availablePrice_€50 to €100PS=Activesoftlaunch

Will deliver when available. Publication date 09 Nov 2024

Product Details
  • Dimensions: 155 x 235mm
  • Publication Date: 19 Oct 2024
  • Publisher: Springer Verlag Singapore
  • Publication City/Country: Singapore
  • Language: English
  • ISBN13: 9789811975868

About Jindong WangYiqiang Chen

Jindong Wang is currently a senior researcher at Microsoft Research Asia. Before that he obtained his PhD from the Institute of Computing Technology Chinese Academy of Sciences in 2019. His main research interests are in transfer learning domain adaptation domain generalization and their applications in ubiquitous computing systems. He has co-published a Chinese-language textbook Introduction to Transfer Learning and numerous papers in leading journals and conferences such as the IEEE TKDE TNNLS ACM TIST NeurIPS CVPR IJCAI UbiComp and ACMMM. He was awarded the best application paper at the IJCAI'19 federated learning workshop and best paper at ICCSE'18. He has served as the publicity chair of IJCAI'19 and the transfer learning session chair of ICDM'19.  Yiqiang Chen is currently a professor at the Institute of Computing Technology Chinese Academy of Sciences. His main research interests are in artificial intelligence and pervasive computing. He has published more than 180 papers in leading journals and conferences such as the IEEE TKDE AAAI and IJCAI. He has served as the general PC chair of the IEEE UIC 2019 PCC 2017 and CWCC 2019. He is a founding committee member of the IEEE wearable and intelligent interaction committee (IWCD) and an associate editor for IEEE TETCI and IJMLC. He has won several best paper awards including best application paper at IJCAI-FL'19 IJIT 15th anniversary best paper award and ICCSE'18 best paper award.

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