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stat.ML2021★ 8 cited
Stopping Criterion for Active Learning Based on Error Stability
Hideaki Ishibashi, Hideitsu Hino
Active learning is a framework for supervised learning to improve the predictive performance by adaptively annotating a small number of samples. To realize efficient active learnin…
stat.ML2020★ 8 cited
Stopping criterion for active learning based on deterministic generalization bounds
Hideaki Ishibashi, Hideitsu Hino
Active learning is a framework in which the learning machine can select the samples to be used for training. This technique is promising, particularly when the cost of data acquisi…