115 citations · 342 across the 14 of their papers we have counts for
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cs.CV2019★ 65 cited
And the Bit Goes Down: Revisiting the Quantization of Neural Networks
Pierre Stock, Armand Joulin, Rémi Gribonval +2
In this paper, we address the problem of reducing the memory footprint of convolutional network architectures. We introduce a vector quantization method that aims at preserving the…
cs.CV2019★ 3 cited
Equi-normalization of Neural Networks
Pierre Stock, Benjamin Graham, Rémi Gribonval +1
Modern neural networks are over-parametrized. In particular, each rectified linear hidden unit can be modified by a multiplicative factor by adjusting input and output weights, wit…