8 citations · 11 across the 6 of their papers we have counts for
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cs.AR2020
FantastIC4: A Hardware-Software Co-Design Approach for Efficiently Running 4bit-Compact Multilayer Perceptrons
Simon Wiedemann, Suhas Shivapakash, Pablo Wiedemann +4
With the growing demand for deploying deep learning models to the "edge", it is paramount to develop techniques that allow to execute state-of-the-art models within very tight and…
cs.LG2020★ 3 cited
Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T)
Arturo Marban, Daniel Becking, Simon Wiedemann +1
Deep neural networks (DNN) have shown remarkable success in a variety of machine learning applications. The capacity of these models (i.e., number of parameters), endows them with…