Introduces induced flows, basis matrices, and tree solutions in graph theory.
Explains the concept of trees in graph theory and the definition of a spanning tree.
Covers the fundamentals of graph theory, including vertices, edges, degrees, walks, connected graphs, cycles, and trees, with a focus on the number of edges in a tree.
Covers the concept of weighted graphs and the Greedy algorithm for finding a minimal spanning tree.
Explores relations between events, disjunctive constraints, and modeling with binary variables in optimization problems.
Distinguishes between subgraphs and induced subgraphs in graph theory, illustrating the construction of minimal spanning trees.
Explores distances on graphs, cut norms, spanning trees, blockmodels, metrics, norms, and ERGMs in network data analysis.
Covers the implementation and analysis of disjoint sets data structure and introduces the concept of minimum spanning trees.
Explores Prim's and Kruskal's algorithms for finding minimum spanning trees in a graph, covering their correctness, implementation, and analysis.
