Advances in Domain Adaptation Theory: Available Theoretical Results - Hardcover

Redko, Ievgen; Morvant, Emilie; Habrard, Amaury; Sebban, Marc; Bennani, Younès

Hardcover

ISBN 10: 178548236X ISBN 13: 9781785482366

Publisher: ISTE Press - Elsevier, 2019

Synopsis

Domain Adaptation Theory: Available Theoretical Results 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

About this title

Review

Focuses on the current results of transfer learning, with an emphasis on field adaptation from a theoretical POV

About the Author

Ievgen Redko is an associate professor at INSA in Lyon since 2016. He obtained his PhD in computer Science, specialized in Data Science in 2015.

Edition details

• Publisher: ISTE Press - Elsevier
• Publication date: 2019
• ISBN 10: 178548236X
• ISBN 13: 9781785482366
• Binding: Hardcover
• Language: English
• Edition number: 1
• Number of pages: 208