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Více informací o knize Advances in Domain Adaptation Theory

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• Anotace
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Anotace knihy

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 learningFocuses on the adaptation of the field from a theoretical point-of-viewDescribes four major families of theoretical results in the literatureSummarizes existing results on adaptation in the fieldProvides tips for future research

Parametry knihy

Zařazení knihy Knihy v angličtině Computing & information technology Computer science Artificial intelligence

• Plný název: Advances in Domain Adaptation Theory
• Autor: Redko Levgen, Amaury Habrard, Emile Morvant
• Jazyk: Angličtina
• Vazba: Pevná
• Počet stran: 208
• EAN: 9781785482366
• ISBN: 178548236X
• ID: 16394735
• Nakladatelství: Elsevier Books
• Hmotnost: 456 g
• Rozměry: 160 × 238 × 17 mm
• Datum vydání: 14. August 2019

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