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Found 2 papers, 1 papers with code
Open-world Semi-supervised Novel Class Discovery
Traditional semi-supervised learning tasks assume that both labeled and unlabeled data follow the same class distribution, but the realistic open-world scenarios are of more complexity with unknown novel classes mixed in the unlabeled set.
An Interpretable Neuron Embedding for Static Knowledge Distillation
The visualization of semantic vectors allows for a qualitative explanation of the neural network.
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