Learning to Learn: Meta-Critic Networks for Sample Efficient Learning||论文讲解
转载：https://zhuanlan.zhihu.com/p/27629294 文章：https://arxiv.org/abs/1706.09529 我们人是基于价值观驱动的动物。我们做什么不做什么都是因为大脑里面有一杆秤在思考哪个更重要。即使有时候非常感性，也是因为感性的时候做那件事的价值最大化了。既然人拥有价值观，我们能不能让AI也拥有价值观，并利用价值观来驱动AI快速学习？ 答案当然是可
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相关文章
- 1. 论文阅读 Prototypical Networks for Few-shot Learning
- 2. 论文阅读笔记《Meta-SGD: Learning to Learn Quickly for Few-Shot Learning》
- 3. node2vec: Scalable Feature Learning for Networks论文解读
- 4. Learning to Learn
- 5. Matching Networks for One Shot Learning论文解读
- 6. 《HARP-Hierarchical Representation Learning for Networks》论文解读
- 7. 元学习Meta Learning/Learning to learn
- 8. Learning how to learn
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- 10. 【Learning both Weights and Connections for Efficient Neural Networks】论文笔记