J. Yoo

OT-CAL: Optimal-Transport-Guided Adaptive Sample Selection for Efficient Visual Learning

OT-CAL is proposed, an adaptive data selection method that automatically adjusts its sampling preferences during training that improves performance on standard visual learning benchmarks and is three times faster training than full-data training.