articleIEEE Transactions on Neural Networks and Learning SystemsJun 21, 2022Closed access

Transfer Adaptation Learning: A Decade Survey

LZLei ZhangXGXinbo Gao

Chongqing University · Chongqing University of Posts and Telecommunications

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Abstract

The world we see is ever-changing and it always changes with people, things, and the environment. Domain is referred to as the state of the world at a certain moment. A research problem is characterized as transfer adaptation learning (TAL) when it needs knowledge correspondence between different moments/domains. TAL aims to build models that can perform tasks of target domain by learning knowledge from a semantic-related but distribution different source domain. It is an energetic research field of increasing influence and importance, which is presenting a blowout publication trend. This article surveys the advances of TAL methodologies in the past decade, and the technical challenges and essential problems…

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259
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24.29
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100%
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433
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2

Topics & keywords

Topics
Keywords
  • Data science
  • Adaptation (eye)
  • Interpretability
  • Computer science
  • Transfer of learning
  • Classifier (UML)
  • Artificial intelligence
  • Credibility
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