# MLSS-2021 Taipei Collaborative Notes
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Welcome to MLSS-2021 Taipei!
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* Visit the official website for more information [MLSS-2021 Taipei](http://ai.ntu.edu.tw/mlss2021/).
* This is a page to enter all the collaborative notes.
* If you have contributed to the notes, you can write down your name after "*Author:*". We may make the collaborative notes public in the further.
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### Week 1
#### 8/2
* [[Lecture] Large scale learning and planning in reinforcement learning](/@MLSS-2021/rktriVTCu)
* [[Industrial Talk] Google Efforts on AI Research and Talent Development](https://hackmd.io/@MLSS-2021/HydLGy4kY)
* [[Lecture] Cost-sensitive Classification: Techniques and Stories](/@MLSS-2021/SJ7b24pRd)
#### 8/3
* [[Lecture] Theory of deep learning](/@MLSS-2021/rkDmQBTCd)
* [[Industrial Talk] Machine Learning as a Services: Challenges and Opportunities](https://hackmd.io/@MLSS-2021/Sy4sfkV1t)
* [[Lecture] Probability Divergences and Generative Models](/@MLSS-2021/r1ko7SaRd)
#### 8/4
* [[Lecture] Neuro-symbolic systems and the history of AI](/@MLSS-2021/BJnmSra0d)
* [[Lecture] Fundamentals and Applications of Deep Reinforcement Learning](/@MLSS-2021/By1_Sr60d)
* [[Industrial Talk] Transform the Beauty Industry through AI + AR: Perfect Corp’s Innovative Vision into the Digital Era](https://hackmd.io/@MLSS-2021/HJoafJ4kK)
* [[Lecture] Optimal transport](/@MLSS-2021/B1s9BSaRO)
#### 8/5
* [[Lecture] Bias and Fairness in NLP](https://hackmd.io/@MLSS-2021/BJmMm1EyF)
* [[Industrial Talk] Developing a World-Class AI Facial Recognition Solution – CyberLink FaceMe®](https://hackmd.io/@MLSS-2021/S1XU7yN1K)
* [[Lecture] Neural Architecture Search and AutoML](https://hackmd.io/@MLSS-2021/SyIsXAOyY)
#### 8/6
* [[Lecture] Holistic Adversarial Robustness for Deep Learning](/@MLSS-2021/ByO3HrTA_)
* [[Industrial Talk] Advantech, Compal Electronics, TAIWAN SHIN KONG SECURITY, Vizuro Taiwan](https://hackmd.io/@MLSS-2021/Hy5gQJ4kF)
* [[Poster] Session 1](https://hackmd.io/@MLSS-2021/SJhPQJNyY)
### Week 2
#### 8/9
* [[Lecture] An introduction to Statistical Learning Theory and PAC-Bayes Analysis](/@MLSS-2021/BkvRSHpAd)
#### 8/10
* [[Lecture] Pre-training for Natural Language Processing](/@MLSS-2021/HJfQUB6Ru)
* [[Lecture] Deep Learning for Speech Processing](/@MLSS-2021/r1GBIrTA_)
#### 8/11
* [[Lecture] Computer Vision](/@MLSS-2021/H1VvISp0d)
* [[Lecture] TinyML and Efficient Deep Learning](/@MLSS-2021/rJRdIrTRO)
#### 8/12
* [[Poster] Session 2](https://hackmd.io/@MLSS-2021/HJOYXk4kY)
* [[Lecture] Meta Learning for Human Language Processing](/@MLSS-2021/SJncISpCO)
#### 8/13
* [[Lecture] Interpretable machine learning](/@MLSS-2021/Syv2LH6Cd)
* [[Lecture] Overview of learning quantum states](/@MLSS-2021/B1WCIrTRd)
### Week 3
#### 8/16
* [[Lecture] ML privacy](/@MLSS-2021/SJ1xvBTR_)
#### 8/17
* [[Poster] Session 3](https://hackmd.io/@MLSS-2021/rki57kEJY)
* [[Lecture] Continual Visual Learning](/@MLSS-2021/SyTWwSpAO)
#### 8/18
* [[Panel Discussion] Trustworthy Machine Learning: Challenges and Opportunities](https://hackmd.io/@MLSS-2021/rkeTmyNyF)
* [[Poster] Session 4](https://hackmd.io/@MLSS-2021/Hy3jmJVyF)
#### 8/19
* [[Lecture] Machine Learning for Dynamic Environment](/@MLSS-2021/Bk2mPBaCO)
* [[Lecture] Geometric Deep Learning](/@MLSS-2021/BJyIPHaCu)
#### 8/20
* [[Panel Discussion] Self-supervised learning for speech](https://hackmd.io/@MLSS-2021/ByzR7J4kK)

###### tags: `MLSS-2021`