This is an advanced graduate course for students who are already familiar with machine learning. The goal is to explore some of the current active research topics in machine learning, through lectures, paper readings and discussions. The topics covered in the course include modern deep learning models and algorithms, representation learning, small sample learning, generative models, and the mathematical theory of deep learning. Students without prerequisites should seek approval from the instructor to take the course.