Shortest Path Problems: Bellman-Ford

Related lectures (30)

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Introduces Dijkstra's algorithm and probabilistic analysis through the Hiring Problem.

Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.

Demonstrates the iterative process of applying Dijkstra's algorithm to find optimal paths.

Covers the concept of graph sketching with a focus on connected components.

Covers the optimization of pseudometrics in graphs, focusing on minimizing pseudometrics and the shortest path metric.

Provides an example of the Bellman-Ford algorithm for finding the shortest path in a graph.

Explores the Bellman-Ford algorithm, its correctness, and practical applications in dynamic networks and real-world scenarios.

Explores dynamic programming through Pascal's Triangle and Floyd's Algorithm.

Introduces differential forms on manifolds, covering tangent bundles and intersection pairings.

Explores dynamic programming with Bellman-Ford, Dijkstra, greedy strategies, and activity scheduling problems.