Learning the Curriculum with Bayesian Optimization for Task-Specific Word Representation Learning

meeting of the association for computational linguistics, pp. 130-139, 2016.

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Abstract:

We use Bayesian optimization to learn curricula for word representation learning, optimizing performance on downstream tasks that depend on the learned representations as features. The curricula are modeled by a linear ranking function which is the scalar product of a learned weight vector and an engineered feature vector that character...More

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