注意下面很多链接需要访问外国网站,无奈国情如此
1. 多目标优化neural architecture search
Searching toward pareto-optimal device-aware neural architectures
链接:
https://arxiv.org/pdf/1808.09830.pdf
2. GAN Lab,浏览器里玩GAN,挺酷的
链接:
https://poloclub.github.io/ganlab/
3. Facebook无监督翻译
Unsupervised machine translation: A novel approach to provide fast, accurate translations for more languages
链接:
https://code.fb.com/ai-research/unsupervised-machine-translation-a-novel-approach-to-provide-fast-accurate-translations-for-more-languages/?utm_campaign=ARCHITECHT&utm_medium=email&utm_source=ARCHITECHT_67
4. RL概述文
A (Long) Peek into Reinforcement Learning
链接:
https://lilianweng.github.io/lil-log/2018/02/19/a-long-peek-into-reinforcement-learning.html
5. RL大神Pieter Abbeel新deck
链接:
https://www.dropbox.com/s/0cs3s55hsuba0ra/2018_08_13__Deep-Learning-to-Learn__GaTech__Abbeel--final.pdf?dl=0&utm_campaign=Artificial%2BIntelligence%2BWeekly&utm_medium=email&utm_source=Artificial_Intelligence_Weekly_85
6. 各种VAE简介
From Autoencoder to Beta-VAE
链接:
https://lilianweng.github.io/lil-log/2018/08/12/from-autoencoder-to-beta-vae.html
7. gradient boosting介绍
How to explain gradient boosting
链接:
http://explained.ai/gradient-boosting/index.html?utm_campaign=Deep%20Learning%20Weekly&utm_medium=email&utm_source=Revue%20newsletter
8. BAIR博文,用想象的目标做RL
Visual Reinforcement Learning with Imagined Goals
链接:
https://bair.berkeley.edu/blog/2018/09/06/rig/
9. 百度发布EZDL,免费,而且是custom model,AutoML的感觉
链接:
http://ai.baidu.com/ezdl/
10. RL 60天培训班资料
链接:
https://github.com/andri27-ts/60_Days_RL_Challenge
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