Active learning with mismatch-first farthest-traversal
Active learning is typically used when unlabeled data is abundant, but labels are expensive or difficult to obtain. It aims at learning an optimal model with a limited labeling budget. Mismatch-first farthest-traversal has been proposed for sound classification and sound event detection. However, it has a good potential to be extended to other problems.