Learning Semantically Coherent and Reusable Kernels in Convolution Neural Nets for Sentence Classification

Madhusudan Lakshmana
Madhusudan Lakshmana
Keerthi Selvaraj
Keerthi Selvaraj

arXiv: Computation and Language, Volume abs/1608.00466, 2016.

Cited by: 1|Views35
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Abstract:

The state-of-the-art CNN models give good performance on sentence classification tasks. The purpose of this work is to empirically study desirable properties such as semantic coherence, attention mechanism and reusability of CNNs in these tasks. Semantically coherent kernels are preferable as they are a lot more interpretable for explaini...More

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