Dense Graphs: From Theory to Applications

Related lectures (29)

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Covers stochastic properties, network structures, models, statistics, centrality measures, and sampling methods in network data analysis.

Introduces the probabilistic method to prove existence results in graph theory.

Covers the Leighton-Rao algorithm for finding the sparsest cut in a graph, focusing on its steps and theoretical foundations.

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

Covers graph properties, representations, and traversal algorithms using BFS and DFS.

Explores Prim's algorithm for minimum spanning trees and introduces the Traveling Salesman Problem.

Explores graph traversal methods, spanning trees, and shortest paths using BFS and DFS.

Covers the fundamentals of connectivity in graph theory, including paths, cycles, and spanning trees.

Explores Breadth-First Search and Dijkstra's algorithm for finding shortest paths in graphs.

Covers Cayley graphs, generators, group examples, and graph structures.