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State-of-the-art computer vision models are mostly trained with supervised learning using human-labeled images, which limits their scalability due to the expensive annotation cost.
Semi-supervised learning by entropy minimization
Yves Grandvalet and Yoshua Bengio · 2004
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Zero-shot learning - the good, the bad and the ugly
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
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Crest: A class-rebalancing self-training framework for imbalanced semi-supervised learning
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