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Learning with not Enough Data Part 1: Semi-Supervised Learning
The performance of supervised learning tasks improves with more high-quality labels available. However, it is expensive to collect a large number of labeled .
Fixmatch sohn
Remixmatch berthelot
Mixmatch berthelot
Nigram ghani
Tarvaninen valpola
Hudelot tami
Dividemix junnan li
Grandvalet bengio
Randaugment cubuk
Junnan li
Smoothness assumptions
Cluster assumptions
Low density separation assumptions
Manifold assumptions
Consistency training
Mean teacher
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