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Robust domain adaptation

Research output: Contribution to journalArticlepeer-review

Abstract

We derive a generalization bound for domain adaptation by using the properties of robust algorithms. Our new bound depends on λ-shift, a measure of prior knowledge regarding the similarity of source and target domain distributions. Based on the generalization bound, we design SVM variants for binary classification and regression domain adaptation algorithms.

Original languageEnglish
Pages (from-to)365-380
Number of pages16
JournalAnnals of Mathematics and Artificial Intelligence
Volume71
Issue number4
DOIs
StatePublished - 1 Aug 2014

Keywords

  • Adaptation
  • Robustness
  • SVM

ASJC Scopus subject areas

  • Applied Mathematics
  • Artificial Intelligence

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