Minimum Spanning TreesCovers the implementation and analysis of disjoint sets data structure and introduces the concept of minimum spanning trees.
Minimal Spanning TreeCovers the concept of weighted graphs and the Greedy algorithm for finding a minimal spanning tree.
Dynamic Programming: KnapsackExplores dynamic programming for the Knapsack problem, discussing strategies, algorithms, NP-hardness, and time complexity analysis.
Max Sum DiversificationExplores maximizing diversity in document selection, graph clique determination, theorems on negative type, and convex optimization.
Introduction to Shortest PathIntroduces the concept of shortest path, discussing weighted paths, Hamiltonian paths, and path optimization algorithms.
Open ProblemsExplores a variety of open problems in graph theory and computational complexity, challenging students to analyze and solve complex issues.
Union-Find and Prim's AlgorithmIntroduces Union-Find data structure and Prim's algorithm for minimum spanning trees in graphs, exploring cuts and historical origins.
Subgraphs vs Induced SubgraphsDistinguishes between subgraphs and induced subgraphs in graph theory, illustrating the construction of minimal spanning trees.
Distances and Motif CountsExplores distances on graphs, cut norms, spanning trees, blockmodels, metrics, norms, and ERGMs in network data analysis.