← Search

Dharmendra S Modha

2 accepted papers

2020

LEARNED STEP SIZE QUANTIZATION

ICLR 2020poster

Deep networks run with low precision operations at inference time offer power and space advantages over high precision alternatives, but need to overcome the challenge of maintaining high accuracy as precision decreases. Here, we present a method for training such networks, Learned Step Size Quantiz…

Cited by 1015SourceScholar
2015

Backpropagation for Energy-Efficient Neuromorphic Computing

NeurIPS 2015spotlight

Solving real world problems with embedded neural networks requires both training algorithms that achieve high performance and compatible hardware that runs in real time while remaining energy efficient. For the former, deep learning using backpropagation has recently achieved a string of successes a…

Cited by 1257SourcePDFScholar