(13)[ICLR16] Net2Net: ACCELERATING LEARNING VIA KNOWLEDGE TRANSFER
计划完成深度学习入门的126篇论文第十三篇，UW的陈天奇和Goodfellow合著针对知识迁移的加速学习Net2Net。 ABSTRACT&INTRODUCTION 摘要 咱们介绍了将存储在一个神经网络中的信息快速传输到另外一个神经网络的技术。主要目的是加速训练一个更大的神经网络。在实际的工做流程中，人们常常在实验和设计过程当中训练许多不一样的神经网络。每一个新模型都是从零开始训练的，因此这是一个
相关文章
- 1. (13)[ICLR16] Net2Net: ACCELERATING LEARNING VIA KNOWLEDGE TRANSFER
- 2. Graph Few-shot learning via Knowledge Transfer
- 3. Transfer Learning[论文合集]
- 4. Paper Note --- Transfer Learning via Dimensionality Reduction
- 5. Transfer Learning for Item Recommendations and Knowledge Graph Completion
- 6. 迁移学习论文阅读：Transfer Learning via Learning to Transfer
- 7. 【distill.&transfer】Deep Face Recognition Model Compression via Knowledge Transfer and Distillation
- 8. transfer learning
- 9. Graphonomy: Universal Human Parsing via Graph Transfer Learning
- 10. 阅读理解《Better and Faster: Knowledge Transfer from Multiple Self-supervised Learning Tasks via Graph D》
- 更多相关文章...
- • ASP Transfer 方法 - ASP 教程
- • PHP is_uploaded_file() 函数 - PHP参考手册
- • Java Agent入门实战（一）-Instrumentation介绍与使用
- • Java Agent入门实战（三）-JVM Attach原理与使用
相关标签/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
最新文章
- 1. 升级Gradle后报错Gradle‘s dependency cache may be corrupt (this sometimes occurs
- 2. Smarter, Not Harder
- 3. mac-2019-react-native 本地环境搭建(xcode-11.1和android studio3.5.2中Genymotion2.12.1 和VirtualBox-5.2.34 )
- 4. 查看文件中关键字前后几行的内容
- 5. XXE萌新进阶全攻略
- 6. Installation failed due to: ‘Connection refused: connect‘安卓studio端口占用
- 7. zabbix5.0通过agent监控winserve12
- 8. IT行业UI前景、潜力如何？
- 9. Mac Swig 3.0.12 安装
- 10. Windows上FreeRDP-WebConnect是一个开源HTML5代理，它提供对使用RDP的任何Windows服务器和工作站的Web访问
欢迎关注本站公众号,获取更多信息
相关文章
- 1. (13)[ICLR16] Net2Net: ACCELERATING LEARNING VIA KNOWLEDGE TRANSFER
- 2. Graph Few-shot learning via Knowledge Transfer
- 3. Transfer Learning[论文合集]
- 4. Paper Note --- Transfer Learning via Dimensionality Reduction
- 5. Transfer Learning for Item Recommendations and Knowledge Graph Completion
- 6. 迁移学习论文阅读：Transfer Learning via Learning to Transfer
- 7. 【distill.&transfer】Deep Face Recognition Model Compression via Knowledge Transfer and Distillation
- 8. transfer learning
- 9. Graphonomy: Universal Human Parsing via Graph Transfer Learning
- 10. 阅读理解《Better and Faster: Knowledge Transfer from Multiple Self-supervised Learning Tasks via Graph D》