PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Robust Domain Adaptation
Yishay Mansour and Mariano Schain
In: isaim 2012, January 9–11, 2012, Fort Lauderdale, FL,USA.

Abstract

We derive a generalization bound for domain adaptation by using the properties of robust algorithms. Our new bound depends on -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.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:8565
Deposited By:Yishay Mansour
Deposited On:12 February 2012