Learning from Semi-Supervised Weak-Label Data理解
Hao-chen Dong, Yu-Feng Li, Zhi-Hua Zhou. 2018 AAAI. 前言 前一阵子读了几篇关于深度学习应用在智慧教育上的论文，对“可解释性”又有了些疑问。于是，这次读了篇使用机器学习方法研究半监督弱标签的论文，换个思路去思考问题。 首先，来看看什么是半监督弱标签问题（semi-supervised weak-label, 以下简称为SSWL）？SSWL是多标签学
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相关文章
- 1. Learning from Uncertainty for Big Data
- 2. Learning from data 练习3.2
- 3. 论文理解《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》笔记
- 6. 研究生课程——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