Dynamical ensemble learning with model-friendly classifiers for domain adaptation

ICPR, pp. 1181-1184, 2012.

Cited by: 15|Views3
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Abstract:

In the domain adaptation research, which recently becomes one of the most important research directions in machine learning, source and target domains are with different underlying distributions. In this paper, we propose an ensemble learning framework for domain adaptation. Owing to the distribution differences between source and target ...More

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