Graph Alignment: Informational and Computational Limits - Lecture 2

Explore the second lecture on Graph Alignment: Informational and Computational Limits delivered by Laurent Massoulié as part of the Discussion Meeting on Data Science: Probabilistic and Optimization Methods. Delve into the complex world of graph alignment, examining both the informational and computational boundaries that shape this field. Gain insights from a leading expert in the area, as Massoulié builds upon the foundations laid in the first lecture to further elucidate the challenges and opportunities in graph alignment. Discover how this topic fits into the broader context of data science, particularly in relation to probabilistic and optimization methods. Engage with cutting-edge research and theoretical frameworks that are driving advancements in this crucial area of study, which has wide-ranging applications in network analysis, bioinformatics, and social network research.

Graph Alignment: Informational and Computational Limits (Lecture-2) by Laurent Massoulié