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Active Supervised Domain Adaptation

  • Avishek Saha
  • Piyush Rai
  • Hal DauméIII
  • Suresh Venkatasubramanian
  • Scott L. DuVall
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6913)

Abstract

In this paper, we harness the synergy between two important learning paradigms, namely, active learning and domain adaptation. We show how active learning in a target domain can leverage information from a different but related source domain. Our proposed framework, Active Learning Domain Adapted (Alda), uses source domain knowledge to transfer information that facilitates active learning in the target domain. We propose two variants of Alda: a batch B-Alda and an online O-Alda. Empirical comparisons with numerous baselines on real-world datasets establish the efficacy of the proposed methods.

Keywords

active learning domain adaptation batch online 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Avishek Saha
    • 1
  • Piyush Rai
    • 1
  • Hal DauméIII
    • 2
  • Suresh Venkatasubramanian
    • 1
  • Scott L. DuVall
    • 3
  1. 1.School of ComputingUniversity of UtahUSA
  2. 2.Department of Computer ScienceUniversity of Maryland CPUSA
  3. 3.VA SLC Healthcare SystemUniversity of UtahUSA

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