Machine Learning on Graphs

Catalog description

Machine learning is a sub-field of Artificial Intelligence that is concerned with the design and analysis of algorithms that "learn" and improve with experience. Machine learning algorithms have traditionally been developed for tabular data. Recent developments in machine learning, including deep learning architectures, have also focused on other types of data, including image, text, time series, and graph data. This course introduces students to machine learning on graph data, which are often used to represent networks such as social and information networks. This course will cover mathematical representations for graphs, measures and algorithms for analyzing graph data, probabilistic models for random graphs, and graph representation learning, including graph embeddings and graph neural networks. Offered as CSDS 346 and CSDS 446 . Prereq: CSDS 340 or CSDS 440 .