Hard Sample Mining: A New Paradigm of Efficient and Robust Model Training

Summary

A survey of hard sample mining (HSM), a paradigm for improving deep learning training efficiency and robustness through representative sample selection. The authors propose unified definitions of hard samples based on sample complexity quantification criteria, a systematic taxonomy of HSM approaches, and identify research frontiers in the field.