Lecture 18: Shortest Paths II: Bellman-Ford, Linear Programming, Difference Constraints
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"Good morning, everyone. Glad you are all here bright and early. I'm counting the days till the TA's outnumber the students. They'll show up. We return to a familiar story. This is part two, the Empire Strikes Back. So last time, our adversary, the graph, came to us with a problem. We have a source, and we had a directed graph, and we had weights on the edges, and they were all nonnegative. And there was happiness. And we triumphed over the Empire by designing Dijkstra's algorithm, and very efficiently finding single source shortest paths, shortest path weight from s to every other vertex...
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