Model Compression and Acceleration Overview
模型壓縮、模型加速 模型壓縮方法： 能夠有效降低參數冗餘減少存儲佔用、通信帶寬、計算複雜度利部署 線性或非線性量化：1/2bits, int8 和 fp16等； 結構或非結構剪枝：deep compression, channel pruning 和 network slimming等； 網絡結構搜索 (NAS: Network Architecture Search)：DARTS, DetNAS
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相關文章
- 1. 深度學習模型壓縮與優化加速（Model Compression and Acceleration Overview）
- 2. 【論文閱讀筆記】---《A Survey of Model Compression and Acceleration for Deep Neural Networks》
- 3. DeepLearning - Overview of Sequence model
- 4. Model Checking Turotial Overview
- 5. Overview and Installation
- 6. Multimedia over IP and Wireless Networks: Compression, Networking, and Systems
- 7. Image and Video Compression Techniques
- 8. Huffman Codes and Data Compression
- 9. 【distill.&transfer】Deep Face Recognition Model Compression via Knowledge Transfer and Distillation
- 10. 1.Overview and Descriptive Statistics