Graph Representation Learning and Applications
Jian Tang · Apr 26, 2019
Date: 2019-04-26 Time: 15:30-16:30 Location: BURNSIDE 1205 Abstract: Graphs, a general type of data structures for capturing interconnected objects, are ubiquitous in a variety of disciplines and domains ranging from computational social science, recommender systems, medicine, bioinformatics to chemistry. Representative examples of real-world graphs include social networks, user-item networks, protein-protein interaction networks, and molecular structures, which are represented as graphs. In this talk, I will introduce our work on learning effective representations of graphs such as learning low-dimensional node representations of large graphs (e.