Construct · 1 fields · 1 citations

domain adaptation: a standalone construct

One name. One construct. A landmark on the map.

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Machine learning

learning a model from a source domain that must perform well on a different target domain, with bounds based on domain divergence.

In machine learning, domain adaptation refers to learning a model from a source domain that must perform well on a different target domain, with bounds based on domain divergence. This meaning comes from Ben-David (2009) in Machine Learning.[1]

Unit
Recovery means
Measured by

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Nearby constructs

transfer6 fields · 16 citationsjingle · one name, six constructs adaptation5 fields · 7 citationsjingle · one word, five constructs divergence4 fields · 4 citationsjingle · one word, four constructs

References

Ben-David, S., Blitzer, J., Crammer, K., Kulesza, A., Pereira, F., & Vaughan, J. W. (2009). A theory of learning from different domains. Machine Learning, 79(1-2), 151-175. https://doi.org/10.1007/s10994-009-5152-4

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