【MLSS 2021 TAIPEI (Machine Learning Summer School)】系列

Speaker: Csaba Szepesvari

Title: Large scale learning and planning in reinforcement learning

Handout

Course Link

Speaker: Hsuan-Tien Lin

Title: Cost-sensitive Classification: Techniques and Stories

Handout

Course Link

Speaker: Jason Lee

Title: Theory of deep learning

Handout

Course Link

Industrial Talk: Appier Inc.

Speaker: Shou-De Lin

Title: Machine Learning as a Services: Challenges and Opportunities

Course Link

Speaker: Henry Kautz

Title: Neuro-symbolic systems and the history of AI

Handout

Course Link

Speaker: Chun-Yi Lee
Title: Fundamentals and Applications of Deep Reinforcement Learning

Handout

Course Link

Industrial Talk: Perfect Corp.
Speaker: Johnny Tseng
Title: Transform the Beauty Industry through AI + AR: Perfect Corp’s Innovative Vision into the Digital Era

Handout

Course Link

Speaker: Marco Cuturi
Title: Optimal transport

Handout

Course Link

Speaker: Kai-Wei Chang

Title: Bias and Fairness in NLP

Handout

Course Link

Industrial Talk: CyberLink Corp.

Speaker: David Lee

Title: Developing a World-Class AI Facial Recognition Solution – CyberLink FaceMe®

Course Link

Speaker: Cho-Jui Hsieh

Title: Neural Architecture Search and AutoML

Handout

Course Link

Speaker: Pin-Yu Chen

Title: Holistic Adversarial Robustness for Deep Learning

Handout

Course Link

Speaker: John Shawe-Taylor

Title: An introduction to Statistical Learning Theory and PAC-Bayes Analysis

Handout

Course Link

Speaker: Hung-Yi Lee

Title: Deep Learning for Speech Processing

Handout

Course Link

Speaker: Philipp Krähenbühl
Title: Computer Vision

Course Link

Speaker: Song Han
Title: TinyML and Efficient Deep Learning

Handout

Course Link

Speakers: Thang Vu, Shang-Wen Li
Title: Meta Learning for Human Language Processing

Handout

Course Link

Speaker: Been Kim
Title: Interpretable machine learning

Handout

Course Link

Speaker: Karteek Alahari
Title: Continual Visual Learning

Handout

Course Link

Speaker: Michael Bronstein
Title: Geometric Deep Learning

Handout

Course Link

Speaker: Shou-De Lin

Title: Machine Learning in Practice – what to do if my ML models fail to achieve a desirable quality ?

Handout

Course Link

Panel Discussion

Panelists:

* Cho-Jui Hsieh

* Pin-Yu Chen

* Soheil Feizi

* Sijia Liu

Title: Trustworthy Machine Learning: Challenges and Opportunities

Handout

Course Link

Panel Discussion

Panelists:

* Shinji Watanabe

* Shang-Wen Li

* Mirco Ravanelli

* Titouan Parcollet

Title:Self-supervised Learning and Universal Modeling for Speech and Audio Processing – Benchmarking and Open-source Toolkits

Handout

Course Link

Speaker: Arthur Gretton
Title: Probability Divergences and Generative Models

Course Link