Proposes LCD and three other hybrid uncertainty-diversity sampling methods for active learning that outperform prior approaches by selecting uncertain yet diverse samples.
How to measure uncertainty in uncertainty sampling for active learning.Machine Learning, 111(1):89–122, 2022
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Balancing Uncertainty and Diversity of Samples: Leveraging Diversity of Least, High Confidence Samples for Effective Active Learning
Proposes LCD and three other hybrid uncertainty-diversity sampling methods for active learning that outperform prior approaches by selecting uncertain yet diverse samples.