Knowledge Projection for Effective Design of Thinner and Faster Deep Neural Networks论文初读
目录 摘要 引言 相关工作 KPN 总览 KPN层设计 多路多阶段训练 迭代删减选择映射路径 实验结果 数据集上的分析 自动路径选择方法的分析 结论 摘要 作者提出了一种teacher-student映射知识蒸馏的方法，在小数据集上有效 teacher和student用来对接的中间层可以通过自适应的方式来选择，这种自适应的方式是以一种迭代的方式通过评估联合损失来完成的 引言
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相关文章
- 1. 论文阅读《Knowledge Projection for Effective Design of Thinner and Faster Deep Neural Networks》
- 2. [论文笔记]Relay Backpropagation for Effective Learning of Deep Convolutional Neural Networks
- 3. 论文阅读：Deep Neural Networks for Object Detection
- 4. [论文解读] Concolic Testing for Deep Neural Networks
- 5. Neural Networks and Deep Learning-引论
- 6. 论文阅读：Aggregated Residual Transformations for Deep Neural Networks（ResNeXt）
- 7. 【论文阅读笔记】---《A Survey of Model Compression and Acceleration for Deep Neural Networks》
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- 9. 《Deep Back-Projection Networks For Super-Resolution》论文阅读之DBPN
- 10. COMPRESSION OF DEEP CONVOLUTIONAL NEURAL NETWORKS FOR FAST AND LOW POWER MOBILE APPLICATIONS论文解读