Graph Theory Basics

Related lectures (30)

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

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

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

Explores expanders, Ramanujan graphs, eigenvalues, Laplacian matrices, and spectral properties.

Covers girth, independence, probability, union bound, sets, and hypergraph recoloring.

Explores the concept of minimizing guardians in graphs through strategic edge selection.

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

Covers the basics of Markov chains and their algorithmic applications.

Explores Ramsey theory, alterations, colorings in graphs, monochromatic matchings, and the significance of large cliques.

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