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Integrated Weak Learning
We introduce a label model that can learn to aggregate weak supervision sources differently for different datapoints and takes into consideration the performance of the end-model during training.
Sample Efficient Model Evaluation
Labelling data is a major practical bottleneck in training and testing classifiers.
One-Shot Learning in Discriminative Neural Networks
We consider the task of one-shot learning of visual categories.
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