Graph Coloring: Basics and Applications

Related lectures (29)

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

Covers the fundamentals of Markov chains and their applications in algorithms, focusing on proper coloring and the Metropolis algorithm.

Explores the Szemerédi Regularity Lemma, e-regularity in bipartite graphs, supergraph structure, and induction techniques.

Explores automorphisms of graphs, focusing on automorphism groups, Cayley-Abels graphs, and quasi-isometry.

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

Covers the independence polynomial of a dependency graph and related concepts such as graph coloring and directed graph properties.

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

Covers the fundamentals of handling networks and centrality measures in graph theory.

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