Papers with Bayes-by-Backprop

1 papers
Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study (D18-1)

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Challenge: Existing studies on Active Learning (AL) for natural language processing have limited data requirements.
Approach: They propose a Bayesian active learning approach that reduces deep learning's data dependence by comparing models and acquisition functions.
Outcome: The proposed approach outperforms i.i.d. baselines and is more efficient than other approaches.

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