Model Compression and Acceleration Overview
模型压缩、模型加速 模型压缩方法： 能够有效降低参数冗余减少存储占用、通信带宽、计算复杂度利部署 线性或非线性量化：1/2bits, int8 和 fp16等； 结构或非结构剪枝：deep compression, channel pruning 和 network slimming等； 网络结构搜索 (NAS: Network Architecture Search)：DARTS, DetNAS
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相关文章
- 1. 深度学习模型压缩与优化加速（Model Compression and Acceleration Overview）
- 2. 【论文阅读笔记】---《A Survey of Model Compression and Acceleration for Deep Neural Networks》
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