activity
20142020
most citedBinarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

2.2k citations · 6.8k across the 9 of their papers we have counts for

collaborators
Showing cs.NEShow all

2 papers · 1 filter

cs.NE2019★ 2 cited

Attention Based Pruning for Shift Networks

Ghouthi Boukli Hacene, Carlos Lassance, Vincent Gripon +2

In many application domains such as computer vision, Convolutional Layers (CLs) are key to the accuracy of deep learning methods. However, it is often required to assemble a large…

cs.NE2016★ 1.4k cited

Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Itay Hubara, Matthieu Courbariaux, Daniel Soudry +2

We introduce a method to train Quantized Neural Networks (QNNs) --- neural networks with extremely low precision (e.g., 1-bit) weights and activations, at run-time. At train-time t…