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cs.LG2025
Uncertainty Herding: One Active Learning Method for All Label Budgets
Wonho Bae, Gabriel L. Oliveira, Danica J. Sutherland
Most active learning research has focused on methods which perform well when many labels are available, but can be dramatically worse than random selection when label budgets are s…
cs.LG2024
Generalized Coverage for More Robust Low-Budget Active Learning
Wonho Bae, Junhyug Noh, Danica J. Sutherland
The ProbCover method of Yehuda et al. is a well-motivated algorithm for active learning in low-budget regimes, which attempts to "cover" the data distribution with balls of a given…
cs.LG2024
Exploring Active Learning in Meta-Learning: Enhancing Context Set Labeling
Wonho Bae, Jing Wang, Danica J. Sutherland
Most meta-learning methods assume that the (very small) context set used to establish a new task at test time is passively provided. In some settings, however, it is feasible to ac…