Statistical Analysis of Networks: Link Prediction and Biclustering

This lecture by the instructor covers the topics of link prediction and biclustering in the context of statistical analysis of network data. It delves into scoring methods for link prediction, logistic regression models, and the use of classifiers to predict missing edges. Additionally, it explores causal inference in networks, estimating treatment effects, and the variance of these effects. The lecture also discusses biclustering, a technique for clustering rows and columns of data matrices simultaneously to identify patterns. Various applications of biclustering in different fields are highlighted, emphasizing the importance of identifying coherent behavior in data matrices.