Explores the equivalence between maximum flow and minimum cut in network theory, demonstrating its applications through examples and edge-disjoint paths.
Covers network flow algorithms, including Max Flow, Min Cut, and Negative Cost Cycle Algorithm, progressing from basic definitions to advanced algorithms like Bellman-Ford and Dijkstra's.
Covers algorithmic paradigms for dynamic graph problems, including dynamic connectivity, expander decomposition, and local clustering, breaking barriers in k-vertex connectivity problems.
