62 citations · 120 across the 10 of their papers we have counts for
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cs.LG2014★ 11 cited
A Method for Stopping Active Learning Based on Stabilizing Predictions and the Need for User-Adjustable Stopping
Michael Bloodgood, K. Vijay-Shanker
A survey of existing methods for stopping active learning (AL) reveals the needs for methods that are: more widely applicable; more aggressive in saving annotations; and more stabl…
cs.LG2014★ 2 cited
Taking into Account the Differences between Actively and Passively Acquired Data: The Case of Active Learning with Support Vector Machines for Imbalanced Datasets
Michael Bloodgood, K. Vijay-Shanker
Actively sampled data can have very different characteristics than passively sampled data. Therefore, it's promising to investigate using different inference procedures during AL t…