76 citations · 218 across the 10 of their papers we have counts for
3 papers · 1 filter
Term Revealing: Furthering Quantization at Run Time on Quantized DNNs
H. T. Kung, Bradley McDanel, Sai Qian Zhang
We present a novel technique, called Term Revealing (TR), for furthering quantization at run time for improved performance of Deep Neural Networks (DNNs) already quantized with con…
Embedded Binarized Neural Networks
Bradley McDanel, Surat Teerapittayanon, H. T. Kung
We study embedded Binarized Neural Networks (eBNNs) with the aim of allowing current binarized neural networks (BNNs) in the literature to perform feedforward inference efficiently…
Distributed Deep Neural Networks over the Cloud, the Edge and End Devices
Surat Teerapittayanon, Bradley McDanel, H. T. Kung
We propose distributed deep neural networks (DDNNs) over distributed computing hierarchies, consisting of the cloud, the edge (fog) and end devices. While being able to accommodate…