Graph Coloring: Basics and Applications

Related lectures (29)

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Explores Belief Propagation in graphical models, factor graphs, spin glass examples, Boltzmann distributions, and graph coloring properties.

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

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

Covers graph algorithms, modeling relationships between objects, and traversal techniques like BFS and DFS.

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

Compares random and symmetrical graph coloring in terms of cluster colorability and equilibrium.

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

Covers graphical models for probabilistic distributions using graphs, nodes, and edges.

Introduces graph theory basics, Ramsey theory, and graph coloring concepts.

Explores Markov chains, focusing on the coloring problem and algorithm analysis.