Learning on Graphs

Speaker:  Nitesh Chawla – Notre Dame, IN, United States
Topic(s):  Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing

Abstract

Graphs are ubiquitous across a variety of use-cases, and have emerged as a powerful means of representing complex systems. Graph Neural Networks have demonstrated exceptional effectiveness in handling graph data; however, there are numerous challenges from multiple data modalities to lack of labeled data. In this talk, I’ll introduce our work on learning from multiple data, and also the ideas of learning from limited data, including few-shot and self-supervised learning. I’ll also discuss applications of these methods. 

About this Lecture

Number of Slides:  45
Duration:  60 minutes
Languages Available:  English
Last Updated: 

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