Learning from Semi-Supervised Weak-Label Data理解
Hao-chen Dong, Yu-Feng Li, Zhi-Hua Zhou. 2018 AAAI. 前言 前一陣子讀了幾篇關於深度學習應用在智慧教育上的論文，對「可解釋性」又有了些疑問。於是，這次讀了篇使用機器學習方法研究半監督弱標籤的論文，換個思路去思考問題。 首先，來看看什麼是半監督弱標籤問題（semi-supervised weak-label, 以下簡稱爲SSWL）？SSWL是多標籤學
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相關文章
- 1. Learning from Uncertainty for Big Data
- 2. Learning from data 練習3.2
- 3. 論文理解《Learning from Synthetic Data for Crowd Counting in the Wild》
- 4. 【Learning from data】Lecture 2_Learning to answer yes or no
- 5. 《AutoAugment: Learning Augmentation Strategies from Data》筆記
- 6. 研究生課程——learning from data——lecture1:introduction
- 7. Communication-Efficient Learning of Deep Networks from Decentralized Data
- 8. Reinforcement Learning for Relation Classification from Noisy Data
- 9. Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation
- 10. [NAS-AutoAug]AutoAugment: Learning Augmentation Strategies from Data