Energy-efficient Amortized Inference with Cascaded Deep Classifiers

10 Oct 2017 Jiaqi Guan Yang Liu Qiang Liu Jian Peng

Deep neural networks have been remarkable successful in various AI tasks but often cast high computation and energy cost for energy-constrained applications such as mobile sensing. We address this problem by proposing a novel framework that optimizes the prediction accuracy and energy cost simultaneously, thus enabling effective cost-accuracy trade-off at test time... (read more)

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