Advances in Domain Adaptation Theory
  • Release Date : 23 August 2019
  • Publisher : Elsevier
  • Genre : Computers
  • Pages : 208 pages
  • ISBN 13 : 9780081023471
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Download or read book entitled Advances in Domain Adaptation Theory by author: Ievgen Redko which was release on 23 August 2019 and published by Elsevier with total page 208 pages . This book available in PDF, EPUB and Kindle Format. Advances in Domain Adaptation Theory gives current, state-of-the-art results on transfer learning, with a particular focus placed on domain adaptation from a theoretical point-of-view. The book begins with a brief overview of the most popular concepts used to provide generalization guarantees, including sections on Vapnik-Chervonenkis (VC), Rademacher, PAC-Bayesian, Robustness and Stability based bounds. In addition, the book explains domain adaptation problem and describes the four major families of theoretical results that exist in the literature, including the Divergence based bounds. Next, PAC-Bayesian bounds are discussed, including the original PAC-Bayesian bounds for domain adaptation and their updated version. Additional sections present generalization guarantees based on the robustness and stability properties of the learning algorithm. Gives an overview of current results on transfer learning Focuses on the adaptation of the field from a theoretical point-of-view Describes four major families of theoretical results in the literature Summarizes existing results on adaptation in the field Provides tips for future research

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Author : Troy McDaniel,Stefano Berretti,Igor D. D. Curcio,Anup Basu
Publisher : Springer Nature
Genre : Computers
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