Domain Adaptation with Structural Correspondence Learning

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Published on October 9, 2007 2:32:03 AM ● Video Link: https://www.youtube.com/watch?v=kH8PCgagaU8

Duration: 59:54

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Google Tech Talks
September, 5 2007

ABSTRACT

Statistical language processing tools are being applied to an
ever-wider and more varied range of linguistic data. Researchers and
engineers are using statistical models to organize and understand
financial news, legal documents, biomedical abstracts, and weblog
entries, among many other domains. Because language varies so widely,
collecting and curating training sets for each different domain is
prohibitively expensive. At the same time, differences in vocabulary
and writing style across domains can cause state-of-the-art supervised
models to dramatically increase in error.

This talk describes structural correspondence learning (SCL), a method
for...