An Empirical study of Binary Neural Networks' Optimisation

ICLR 2019 Milad AlizadehJavier Fernández-MarquésNicholas D. LaneYarin Gal

Binary neural networks using the Straight-Through-Estimator (STE) have been shown to achieve state-of-the-art results, but their training process is not well-founded. This is due to the discrepancy between the evaluated function in the forward path, and the weight updates in the back-propagation, updates which do not correspond to gradients of the forward path... (read more)

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