Graph-structured data is central to many real-world problems, encompassing domains such as recommender systems, social network analysis, and computational biology. This workshop offers a comprehensive introduction to graph machine learning, covering foundational concepts and state-of-the-art techniques. Participants will learn about graph representation learning and graph neural networks, with a focus on practical applications in the aforementioned areas. Through lectures and discussions, attendees will gain insights into how graph machine learning is transforming diverse fields. This workshop is designed for researchers, practitioners, and students seeking to understand and apply graph-based methodologies to solve complex challenges.
- Instructor: Jundong Li