Quarter
Spring 2021
Instructor/s
Course Type
Special Topics Course
Course Area
Foundations
Enrollment Code
65078
Location
ON LINE
Units
4
Day and Time
T/R 11 am - 12:50 pm
Course Description

Machine learning on graphs has emerged as an important research topic that finds applications in many domains including social networks, infrastructure design and maintenance, drug discovery, brain networks, and material design. This course will discuss methods to encode graphs (static/dynamic, attributed, undirected/directed, single/ensemble) into low-dimensional spaces to facilitate machine learning. Specific topics include random walks, kernels, spectral analysis, generative models, node embedding, subgraph embedding, and graph neural networks.