An Improvement to the Domain Adaptation Bound in a PAC-Bayesian context

January 13, 2015 ยท Declared Dead ยท ๐Ÿ› Neural Information Processing Systems

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Authors Pascal Germain, Amaury Habrard, Francois Laviolette, Emilie Morvant arXiv ID 1501.03002 Category stat.ML: Machine Learning (Stat) Cross-listed cs.LG Citations 0 Venue Neural Information Processing Systems Last Checked 4 months ago
Abstract
This paper provides a theoretical analysis of domain adaptation based on the PAC-Bayesian theory. We propose an improvement of the previous domain adaptation bound obtained by Germain et al. in two ways. We first give another generalization bound tighter and easier to interpret. Moreover, we provide a new analysis of the constant term appearing in the bound that can be of high interest for developing new algorithmic solutions.
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