Graph Algorithms II: Traversal and Paths

Related lectures (28)

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Covers graphical models for probabilistic distributions using graphs, nodes, and edges.

Explores Breadth-First Search and Dijkstra's algorithm for finding shortest paths in graphs.

Covers the fundamentals of connectivity in graph theory, including paths, cycles, and spanning trees.

Explores Prim's and Kruskal's algorithms for finding minimum spanning trees in a graph, covering their correctness, implementation, and analysis.

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

Introduces graph theory basics, graph representation methods, and traversal algorithms like BFS and DFS.

Introduces graph theory, network flows, and flow conservation laws with practical examples and theorems.

Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.

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

Explores dynamic programming strategies for finding shortest paths in networks with various algorithms and complexities.