Ford-Fulkerson Method: Disjoint-set Data Structures

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Explores the Ford-Fulkerson method, max-flow, applications of max-flow, and the disjoint-set data structure.

Introduces unweighted bipartite matching and its solution using linear programming and the simplex method.

Discusses the Ford-Fulkerson method and strongly connected components in graph algorithms.

Discusses Union-Find data structures and Minimum Spanning Trees, covering algorithms and their applications in network design and optimization.

Covers optimization algorithms, stable matching, and Big-O notation for algorithm efficiency.

Explores the Max-flow Min-cut theorem, integral capacities, Ford-Fulkerson method, bipartite matching, and edge-disjoint paths.

Covers the concept of matroids, focusing on matroid intersection and the properties of subsets of a ground set.

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Explores the computation of mean field and effective field in message passing algorithms.

Covers exercises on the spin model, independent set, matching, and increasing functions.

Covers the generalities of functions, including the definition of an application between sets and the uniqueness of elements in the image set.

Explores the optimality of the greedy change-making algorithm and the stability of maximum matching.

Discusses graph algorithms, focusing on flow networks and strongly connected components.

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Explores linear programming duality, covering constraints, variables, solutions, and the relationship between primal and dual LP.

Covers the concept of stable matchings and the Gale-Shapley algorithm.

Covers linear programming, weighted bipartite matching, and vertex cover problems in optimization.

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Explores the Swiss political system, including proportional representation, direct democracy, and recent popular initiatives.

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