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method ID: uncertaintysampling

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Active Learning with Sampling by Uncertainty and Density for Word Sense Disambiguation and Text Classification

Authors: nan

Publication: TIPSTER (2008)

DOI: nan

This paper addresses two issues of active learning. Firstly, to solve a problem of uncertainty sampling that it often fails by selecting outliers, this paper presents a new selective sampling …...

6195

Multi-Criteria-Based Strategy to Stop Active Learning for Data Annotation

Authors: nan

Publication: TIPSTER (2008)

DOI: nan

In this paper, we address the issue of de- ciding when to stop active learning for building a labeled training corpus. Firstly, this paper presents a new stopping crite- rion, …...

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Active Learning by Acquiring Contrastive Examples

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DOI: nan

AbstractCommon acquisition functions for active learning use either uncertainty or diversity sampling, aiming to select difficult and diverse data points from the pool of unlabeled data, respectively. In this work, …...

32048

Adapting Coreference Resolution Models through Active Learning

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractNeural coreference resolution models trained on one dataset may not transfer to new, low-resource domains. Active learning mitigates this problem by sampling a small subset of data for annotators to …...

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Mind the User! Measures to More Accurately Evaluate the Practical Value of Active Learning Strategies

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Publication: TIPSTER (2023)

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AbstractOne solution to limited annotation budgets is active learning (AL), a collaborative process of human and machine to strategically select a small but informative set of examples. While current measures …...

19928