Graph Alignment: Informational and Computational Limits - Lecture 1

Explore the fundamental concepts of graph alignment in this lecture by Laurent Massoulié, part of the Data Science: Probabilistic and Optimization Methods discussion meeting. Delve into the informational and computational limits of graph alignment, a crucial topic in data science and network analysis. Gain insights from Massoulié's expertise as he discusses the theoretical foundations and practical implications of aligning complex graph structures. Learn about the challenges and constraints faced when attempting to match nodes across different graphs, and understand the mathematical frameworks used to analyze these problems. This lecture provides a solid foundation for researchers, data scientists, and students interested in graph theory, network analysis, and their applications in modern data science.

Graph Alignment: Informational and Computational Limits (Lecture-1) by Laurent Massoulié