Correction to: Batch mode active learning via adaptive criteria weights
نویسندگان
چکیده
منابع مشابه
Discriminative Batch Mode Active Learning
Active learning sequentially selects unlabeled instances to label with the goal of reducing the effort needed to learn a good classifier. Most previous studies in active learning have focused on selecting one unlabeled instance to label at one time while retraining in each iteration. Recently a few batch mode active learning approaches have been proposed that select a set of most informative un...
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Active learning can lead to a dramatic reduction in labeling effort. However, in many practical implementations (such as crowdsourcing, surveys, high-throughput experimental design), it is preferable to query labels for batches of examples to be labelled in parallel. While several heuristics have been proposed for batch-mode active learning, little is known about their theoretical performance. ...
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Active learning has been proven to be quite effective in reducing the human labeling efforts by actively selecting the most informative examples to label. In this paper, we present a batch-mode active learning method based on logistic regression. Our key motivation is an out-of-sample bound on the estimation error of class distribution in logistic regression conditioned on any fixed training sa...
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ژورنال
عنوان ژورنال: Applied Intelligence
سال: 2020
ISSN: 0924-669X,1573-7497
DOI: 10.1007/s10489-020-02146-9