A theoretical framework for deep transfer learning

DOI10.1093/imaiai/iaw008zbMath1380.68333OpenAlexW2342750929MaRDI QIDQ4603722

Lior Wolf, Tamir Hazan, Tomer Galanti

Publication date: 19 February 2018

Published in: Information and Inference (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/75f24d175c0f30138063afc841e825ff211090c3

zbMATH Keywords

PAC learningtransfer learningdeep learningPAC-Bayesian

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• ImageNet
• DeepFace
• AlexNet

Cites Work

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• A theory of learning from different domains
• On the density of families of sets
• Learnability and the Vapnik-Chervonenkis dimension
• Sample Selection Bias Correction Theory
• A theory of the learnable
• 10.1162/153244302760200704
• Understanding Machine Learning
• On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities

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