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Evaluation of Deep Gaussian Processes for Text Classification
With the tremendous success of deep learning models on computer vision tasks, there are various emerging works on the Natural Language Processing (NLP) task of Text Classification using parametric models.
Learning Multi-Sense Word Distributions using Approximate Kullback-Leibler Divergence
We propose to learn the Gaussian mixture representation of words using a Kullback-Leibler (KL) divergence based objective function.
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