注意下面很多链接需要访问外国网站,无奈国情如此
1. Google开源RL快速原型框架Dopamine
Introducing a New Framework for Flexible and Reproducible Reinforcement Learning Research
链接:
https://ai.googleblog.com/2018/08/introducing-new-framework-for-flexible.html
2. Google Assistant支持同时语言混搭对话
Teaching the Google Assistant to be Multilingual
链接:
https://ai.googleblog.com/2018/08/Multilingual-Google-Assistant.html
3. Google TPU动画介绍
What makes TPUs fine-tuned for deep learning?
链接:
https://cloud.google.com/blog/products/ai-machine-learning/what-makes-tpus-fine-tuned-for-deep-learning
动画展示:
https://tpudemo.com/
4. Uber用深度学习替代一般机器学习做客服ticket
Scaling Uber’s Customer Support Ticket Assistant (COTA) System with Deep Learning
链接:
https://eng.uber.com/cota-v2/
5. BAIR文章,用RL快速学习机械手动作
Dexterous Manipulation with Reinforcement Learning: Efficient, General, and Low-Cost
链接:
https://bair.berkeley.edu/blog/2018/08/31/dexterous-manip/
6. federated learning介绍
链接:
https://florian.github.io/federated-learning/
7. 3D物体
Beyond the pixel plane: sensing and learning in 3D
链接:
https://thegradient.pub/beyond-the-pixel-plane-sensing-and-learning-in-3d/
8. NLP泛化问题
NLP’s generalization problem, and how researchers are tackling it
链接:
https://thegradient.pub/frontiers-of-generalization-in-natural-language-processing/
9. 重现论文实现,RL learn2learn经典算法MAML和Reptile
Paper repro: Deep Metalearning using “MAML” and “Reptile”
链接:
https://towardsdatascience.com/paper-repro-deep-metalearning-using-maml-and-reptile-fd1df1cc81b0
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