8 citations · 16 across the 2 of their papers we have counts for
3 papers
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…
cs.HC2021
Visual analytics of set data for knowledge discovery and member selection support
Ryuji Watanabe, Hideaki Ishibashi, Tetsuo Furukawa
Visual analytics (VA) is a visually assisted exploratory analysis approach in which knowledge discovery is executed interactively between the user and system in a human-centered ma…
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…