Uncertainty Herding weights coverage by model uncertainty and adapts two parameters so it matches or beats specialized active learning methods at both low and high label budgets.
Active distance-based clustering using k-medoids
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
method 1
citation-polarity summary
fields
cs.LG 1years
2024 1verdicts
CONDITIONAL 1roles
method 1polarities
use method 1representative citing papers
citing papers explorer
-
Uncertainty Herding: One Active Learning Method for All Label Budgets
Uncertainty Herding weights coverage by model uncertainty and adapts two parameters so it matches or beats specialized active learning methods at both low and high label budgets.