Papers with quatization-aware training
On-device Structured and Context Partitioned Projection Networks (P19-1)
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| Challenge: | A challenge in on-device text classification is to build highly accurate models that fit in small memory footprint and have low latency. |
| Approach: | They propose an on-device neural network which learns compact projection vectors from raw text using structured and context-dependent partition projections. |
| Outcome: | The proposed model outperforms baseline models and surpasses RNN, CNN and BiLSTM models on dialog act and intent prediction. |