Papers with multi-label and multi-class classification tasks

1 papers
Towards Integration of Statistical Hypothesis Tests into Deep Neural Networks (P19-1)

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Challenge: Existing approaches for text classification are lexicallevel features with Naive Bayes or Support Vector Machines (SVM) .
Approach: They propose a deep-learning model that uses label descriptions to train texts and their labels for multi-label and multi-class classification tasks.
Outcome: The proposed model improves on one set with a high margin and on all other sets with competitive results.

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