Learning Beyond Predefined Label Space via Bayesian Nonparametric Topic Modelling

ECML/PKDD, pp. 148-164, 2016.

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Abstract:

In real world machine learning applications, testing data may contain some meaningful new categories that have not been seen in labeled training data. To simultaneously recognize new data categories and assign most appropriate category labels to the data actually from known categories, existing models assume the number of unknown new cate...More

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