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Found 5 papers, 1 papers with code
OFU@SMM4H’22: Mining Advent Drug Events Using Pretrained Language Models
We describe in this paper our proposed systems for the Social Media Mining for Health 2022 shared task 1.
Minority Class Oriented Active Learning for Imbalanced Datasets
Here, we introduce a new active learning method which is designed for imbalanced datasets.
A Comparative Study of Calibration Methods for Imbalanced Class Incremental Learning
Since memory is bounded, old classes are learned with fewer images than new classes and an imbalance due to incremental learning is added to the initial dataset imbalance.
Optimizing Active Learning for Low Annotation Budgets
It consists in learning a model on a small amount of annotated data (annotation budget) and in choosing the best set of points to annotate in order to improve the previous model and gain in generalization.
Active Class Incremental Learning for Imbalanced Datasets
Most existing algorithms make two strong hypotheses which reduce the realism of the incremental scenario: (1) new data are assumed to be readily annotated when streamed and (2) tests are run with balanced datasets while most real-life datasets are actually imbalanced.
