Robust domain adaptation

Robust domain adaptation

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 binar...

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Veröffentlicht in:Annals of mathematics and artificial intelligence 2014-08, Vol.71 (4), p.365-380
Hauptverfasser: Mansour, Yishay, Schain, Mariano
Format: Artikel
Sprache:eng
Schlagworte:
Adaptation
Algorithms
Artificial Intelligence
Complex Systems
Computer Science
Mathematics
Robustness
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Zusammenfassung: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.
ISSN:1012-2443
1573-7470
DOI:10.1007/s10472-013-9391-5