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Complexity of Representations in Deep Learning
Motivated by the need to better understand the inner working of a deep neural network, we analyze the effectiveness of the learned representations in separating the classes from a data complexity perspective.
Iterative Data Programming for Expanding Text Classification Corpora
Real-world text classification tasks often require many labeled training examples that are expensive to obtain.
Bootstrapping Conversational Agents With Weak Supervision
We report on a user study that shows positive user feedback for this new approach to build conversational agents, and demonstrates the effectiveness of using data programming for auto-labeling.
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