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Max-flow Min-cut Theorem
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Algorithms: Stable Matchings
Covers the concept of stable matchings and the Gale-Shapley algorithm.
Algorithms: Stable Matchings
Covers the concept of stable matchings and the Gale-Shapley algorithm.
Graph Theory and Network Flows
Introduces graph theory, network flows, and flow conservation laws with practical examples and theorems.
Max Flav-Min Cut in Directed Graphs
Covers the concept of maximum flow-minimum cut in directed graphs with capacity constraints.
Bounded Network Flow: Solvable Minult-Maxcret Problem
Covers solving bounded network flow problems by adjusting flow capacities and constraints, including binary programs.
Network Flow Algorithms
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.
Low Diameter Random Partitioning
Discusses Low Diameter Randomized Decomposition and graph partitioning for edge cuts and coloring.
Sparsest Cut: Bourgain's Theorem
Explores Bourgain's theorem on sparsest cut in graphs, emphasizing semimetrics and cut optimization.
Graph Mining: Modularity and Community Detection
Explores community detection in graphs using modularity and edge betweenness.
Max-Flow Min-Cut
Explores the Ford Fulkerson algorithm, Max-Flow Min-Cut theorem, Incidence matrix, and network optimization complexity.
