2019
Stochastic Data-driven Hardware Resilience to Efficiently Train Inference Models for Stochastic Hardware Implementations
ICASSP 2019accepted
Machine-learning algorithms are being employed in an increasing range of applications, spanning high-performance and energy-constrained platforms. It has been noted that the statistical nature of the algorithms can open up new opportunities for throughput and energy efficiency, by moving hardware in…