Statistical Analysis of Network Data

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Related lectures (29)

Graphical Models: Probability Distributions and Factor Graphs Log in to Mediaspace to watch this video

Covers graphical models for probability distributions and factor graphs representation.

Graph Theory and Network Flows Log in to Mediaspace to watch this video

Introduces graph theory, network flows, and flow conservation laws with practical examples and theorems.

Graph Algorithms: Modeling and Representation Log in to Mediaspace to watch this video

Covers the basics of graph algorithms, focusing on modeling and representation of graphs in memory.

Graphs and Networks: Basics and Applications Log in to Mediaspace to watch this video

Introduces the basics of graphs and networks, covering definitions, paths, trees, flows, circulation, and spanning trees.

Distances and Motif Counts Log in to Mediaspace to watch this video

Explores distances on graphs, cut norms, spanning trees, blockmodels, metrics, norms, and ERGMs in network data analysis.

Graph Algorithms: Basics Log in to Mediaspace to watch this video

Introduces the basics of graph algorithms, covering traversal, representation, and data structures for BFS and DFS.

Convergence of Random Walks Log in to Mediaspace to watch this video

Explores the convergence of random walks on graphs and the properties of weighted adjacency matrices.

Graphs: BFS Log in to Mediaspace to watch this video

Introduces elementary graph algorithms, focusing on Breadth-First Search and Depth-First Search.

Sparsest Cut: ARV Theorem Log in to Mediaspace to watch this video

Covers the proof of the Bourgain's ARV Theorem, focusing on the finite set of points in a semi-metric space and the application of the ARV algorithm to find the sparsest cut in a graph.

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