STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables

1 code implementation • 2 Mar 2023 • Jaehyun Nam, Jihoon Tack, Kyungmin Lee, Hankook Lee, Jinwoo Shin

Learning with few labeled tabular samples is often an essential requirement for industrial machine learning applications as varieties of tabular data suffer from high annotation costs or have difficulties in collecting new samples for novel tasks.

Few-Shot Learning