論文閱讀筆記《Meta-Learning of Neural Architectures for Few-Shot Learning》
核心思想 本文提出一種基於參數優化的小樣本學習算法（MetaNAS）。本文最重要的改進就是將神經架構搜索（neural architecture search，NAS）引入到小樣本學習算法中，簡單地理解就是MAML和Reptile等元學習算法，是在確定網絡結構的基礎上，通過元訓練的方式獲得較好的初始化參數，而本文引入NAS後，不僅要對初始化參數進行學習，而且要對網絡結構參數進行學習。爲了實現這
相關文章
- 1. [論文閱讀筆記] Massive Exploration of Neural Machine Translation Architectures
- 2. 【論文筆記】Neural Architectures for Named Entity Recognition
- 3. Machine Learning & Deep Learning 論文閱讀筆記
- 4. 論文筆記 Neural Architectures for Named Entity Recognition
- 5. 論文閱讀筆記（一）：Learning Dual Convolutional Neural Networks for Low-Level Vision
- 6. 論文《Learning both Weights and Connections for Efficient Neural Network》閱讀筆記
- 7. 《Bag of Tricks for Image Classification with Convolutional Neural Networks》論文閱讀筆記
- 8. DeepLearning論文閱讀筆記(一):Cyclical Learning Rates for Training Neural Networks(CLR)
- 9. 論文閱讀筆記《Edge-Labeling Graph Neural Network for Few-shot Learning》
- 10. Deep Residual Learning for Image Recognition--ResNet論文閱讀筆記
- 更多相關文章...
- • RSS 閱讀器 - RSS 教程
- • PHP 實例 - AJAX RSS 閱讀器 - PHP教程
- • Tomcat學習筆記（史上最全tomcat學習筆記）
- • JDK13 GA發佈：5大特性解讀
相關標籤/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。
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. [論文閱讀筆記] Massive Exploration of Neural Machine Translation Architectures
- 2. 【論文筆記】Neural Architectures for Named Entity Recognition
- 3. Machine Learning & Deep Learning 論文閱讀筆記
- 4. 論文筆記 Neural Architectures for Named Entity Recognition
- 5. 論文閱讀筆記（一）：Learning Dual Convolutional Neural Networks for Low-Level Vision
- 6. 論文《Learning both Weights and Connections for Efficient Neural Network》閱讀筆記
- 7. 《Bag of Tricks for Image Classification with Convolutional Neural Networks》論文閱讀筆記
- 8. DeepLearning論文閱讀筆記(一):Cyclical Learning Rates for Training Neural Networks(CLR)
- 9. 論文閱讀筆記《Edge-Labeling Graph Neural Network for Few-shot Learning》
- 10. Deep Residual Learning for Image Recognition--ResNet論文閱讀筆記