John V. Arthur

Backpropagation for Energy-Efficient Neuromorphic Computing

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…