805 citations · 1.2k across the 10 of their papers we have counts for
Showing 2018Show all
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cs.LG2018★ 3 cited
Low Precision Policy Distillation with Application to Low-Power, Real-time Sensation-Cognition-Action Loop with Neuromorphic Computing
Jeffrey L Mckinstry, Davis R. Barch, Deepika Bablani +5
Low precision networks in the reinforcement learning (RL) setting are relatively unexplored because of the limitations of binary activations for function approximation. Here, in th…
cs.CV2018★ 43 cited
Discovering Low-Precision Networks Close to Full-Precision Networks for Efficient Embedded Inference
Jeffrey L. McKinstry, Steven K. Esser, Rathinakumar Appuswamy +4
To realize the promise of ubiquitous embedded deep network inference, it is essential to seek limits of energy and area efficiency. To this end, low-precision networks offer tremen…