Research map / Label-efficient and robust learning / Semi-supervised learning
Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add input-consistency regularization while fitting pseudolabels | Self-training with deep networks · Semi-supervised learning and unsupervised domain adaptation | ground-truth classification error | Helped |
| Enforce input consistency and require each predicted class to have sufficient probability | Unsupervised classifier · Unsupervised learning | permutation-invariant classification error | Helped |
Closest papers by meaning
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