Dataset Distillation for Audio Classification: A Data-Efficient Alternative to Active Learning

This paper introduces an approach that leverages dataset distillation as an alternative strategy to active learning to address the challenge of data efficiency in real-world audio classification tasks and achieves up to a ∼ 3,000x reduction in data points.