Graph Theory Fundamentals

Related lectures (29)

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

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

Covers graphical models for probability distributions and factor graphs representation.

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

Introduces spanning trees in graphs and the Minimum Spanning Tree problem, exploring efficient algorithms for optimal decision-making.

Covers polynomial identity testing using oracles and random point evaluation, with applications in graph theory and algorithmic aspects.

Explores Cheeger's inequalities for random walks on graphs and their implications.

Covers topics like DFS output, edge classification, acyclic graphs, correctness, time analysis, SCCs, and the Topological Sort algorithm.

Explores the Stein algorithm for polynomial identity testing and the minimization of a cut problem.