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Related lectures (27)

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Explores Bourgain's theorem on sparsest cut in graphs, emphasizing semimetrics and cut optimization.

Focuses on fixed points in graph theory and their implications in algorithms and analysis.

Explores partial derivatives and their role in determining tangents to graphs.

Covers handling network data, types of graphs, centrality measures, and properties of real-world networks.

Explores derivatives, tangents, and elementary function rules in general mathematics.

Covers the properties and operations of convex functions.

Explores pseudorandomness theory, AI challenges, pseudo-random graphs, random walks, and matrix properties.

Introduces network data structures, models, and analysis techniques, emphasizing permutation invariance and Erdős-Rényi networks.

Explores finding the equation of the tangent line to a function's graph at a point.

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