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Using Pre-trained Full-Precision Models to Speed Up Training Binary Networks For Mobile Devices

Binary Neural Networks (BNNs) are well-suited for deploying Deep Neural Networks (DNNs) to small embedded devices but state-of-the-art BNNs need to be trained from scratch. We show how weights from a trained full-precision model can be used to speed-up training binary networks. We show that for CIFAR-10, accuracies within 1% of the full-precision model can be achieved in just 5 epochs.

Milad Alizadeh, Nicholas D. Lane, Yarin Gal
16th ACM International Conference on Mobile Systems (MobiSys), 2018
[Abstract] [BibTex]

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