Algorithms on Graphs. 3 credits, 3 contact hours

Catalog description

Prerequisites: CS 610 , or CS 435 , or doctoral student status, or instructor permission. Graphs are a ubiquitous type of data structure, with multiple scientific and industrial applications. This course covers various old and new graph algorithms with a focus on efficiency and practicality. Topics include: shortest paths, random walks and diffusion, unsupervised and supervised node clustering, hierarchical graph clustering, graph partitioning based on graph matrices, discovering and counting graph substructures, and sampling methods for graph sparsification.