9 citations · 14 across the 5 of their papers we have counts for
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cs.LG2019
Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks
Charbel Sakr, Naigang Wang, Chia-Yu Chen +4
Efforts to reduce the numerical precision of computations in deep learning training have yielded systems that aggressively quantize weights and activations, yet employ wide high-pr…
cs.LG2018★ 9 cited
Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm
Charbel Sakr, Naresh Shanbhag
The high computational and parameter complexity of neural networks makes their training very slow and difficult to deploy on energy and storage-constrained computing systems. Many…