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https://arxiv.org/abs/2003.05891v1 SASL: Saliency-Adaptive Sparsity Learning for Neural Network Acceleration Accelerating the inference speed of CNNs is critical to their deployment in real-world applications. Among all the pruning approaches, those implementing a sparsity learning framework have shown to be effective as they learn and prune the models in an end- arxiv.org abstract 본 논문은 CNN의 추론..