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Self-Governing Neural Networks for On-Device Short Text Classification
2018
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
Deep neural networks reach state-of-the-art performance for wide range of natural language processing, computer vision and speech applications. Yet, one of the biggest challenges is running these complex networks on devices such as mobile phones or smart watches with tiny memory footprint and low computational capacity. We propose on-device Self-Governing Neural Networks (SGNNs), which learn compact projection vectors with local sensitive hashing. The key advantage of SGNNs over existing work
doi:10.18653/v1/d18-1092
dblp:conf/emnlp/RaviK18
fatcat:hieuxynlxbacfahkh3bfs5b2a4