Unsupervised Search-based Structured Prediction

Hal Daumé III

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arXiv · 0906.5151

Unsupervised Search-based Structured Prediction

Hal Daumé III

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Abstract

We describe an adaptation and application of a search-based structured prediction algorithm "Searn" to unsupervised learning problems. We show that it is possible to reduce unsupervised learning to supervised learning and demonstrate a high-quality unsupervised shift-reduce parsing model. We additionally show a close connection between unsupervised Searn and expectation maximization. Finally, we demonstrate the efficacy of a semi-supervised extension. The key idea that enables this is an application of the predict-self idea for unsupervised learning.

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Hal Daumé III. 2009-06-28. Unsupervised Search-based Structured Prediction. https://arxiv.org/abs/0906.5151

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