EagleEye: Fast Sub-net Evaluation for Efficient Neural Network Pruning（论文阅读）
目录 说明 动机 贡献 方法 发现 EagleEye剪枝算法 实验 实验1- 相关性的定量分析 实验2-基于自适应BN的评估方法的通用性 实验3-从修剪候选中选择最佳修剪策略的计算成本 实验4-Effectiveness of our proposed method 总结与讨论 说明 找出训练好的深度神经网络(DNN)的计算冗余部分是剪枝算法要解决的关键问题。许多算法都试图通过引入各种评估方法来预
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相关文章
- 1. 论文阅读-Fast Algorithms for Convolutional Neural Networks
- 2. 论文《Learning both Weights and Connections for Efficient Neural Network》阅读笔记
- 3. 【论文阅读笔记】ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
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