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LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views
By combining two complementing models, LEVI effectively suppresses problematic features in both the fine-tuning data and pre-trained model and preserves useful features for new tasks.
A new semi-supervised inductive transfer learning framework: Co-Transfer
In each round of co-transfer, each group of TrAdaBoost classifiers are refined using the carefully labeled data.
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