Robust domain adaptation

Yishay Mansour; Mariano Schain

Robust domain adaptation

Yishay Mansour, Mariano Schain

School of Computer Science

Tel Aviv University

Research output: Contribution to conference › Paper › peer-review

8 Scopus citations

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 language	English
State	Published - 2012
Event	International Symposium on Artificial Intelligence and Mathematics, ISAIM 2012 - Fort Lauderdale, FL, United States Duration: 9 Jan 2012 → 11 Jan 2012

Conference

Conference	International Symposium on Artificial Intelligence and Mathematics, ISAIM 2012
Country/Territory	United States
City	Fort Lauderdale, FL
Period	9/01/12 → 11/01/12

Cite this

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AU - Schain, Mariano

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T2 - International Symposium on Artificial Intelligence and Mathematics, ISAIM 2012

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Robust domain adaptation

Abstract

Conference

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