Machine Learning on Geometrical Data

CSE291-C00 - Winter 2019


Welcome to the course!

General Information

Times & Places
TuTh 3:30PM - 4:50PM, EBU3B 2154

Course Staff

Name Email Office Hours Location
Instructor Hao Su 3:00PM-4:00PM, Mo CSE Building 4114
Course Assistant Meng Song 11:00AM-12:00PM, Th CSE Building 4127


This is a graduate level course to cover core concepts and algorithms of geometry that are being used in computer vision and machine learning. This course is a combination of instructor lecturing (half of the classes) and student presentation (the other half of the classes). For the instructor lecturing part, I will cover key concepts of differential geometry, the usage of geometry in computer graphics, vision, and machine learning, in particular, deep learning. For the student presentation part, I will advise students to read and present state-of-the-art algorithms for taking the geometric view to analyze data and the advanced tools to understand geometric data. Students are required to do a course project in pairs.


Background assumed includes basic material in linear algebra, optimization, machine learning, and graphical models.

Grading (tentative)


The planned syllabus is as below. Certain contents may be added or removed based upon the interactions in class and other situations.