# Gone Fishing: Neural Active Learning with Fisher Embeddings

@inproceedings{Ash2021GoneFN, title={Gone Fishing: Neural Active Learning with Fisher Embeddings}, author={Jordan T. Ash and Surbhi Goel and Akshay Krishnamurthy and Sham M. Kakade}, booktitle={NeurIPS}, year={2021} }

There is an increasing need for effective active learning algorithms that are compatible with deep neural networks. This paper motivates and revisits a classic, Fisher-based active selection objective, and proposes BAIT, a practical, tractable, and high-performing algorithm that makes it viable for use with neural models. BAIT draws inspiration from the theoretical analysis of maximum likelihood estimators (MLE) for parametric models. It selects batches of samples by optimizing a bound on the…

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