karp

Getty is big enough that they should be able to get Karp on the horn and do this properly.

How about substring searching: Boyer- Moore searches backwards, Rabin Karp computes hashes while others simulate automata.

That said, Karp flips between handling it well and not handling it well in the comments.

Tumblr's David Karp dropped out of high school.

A russian (soviet) mathematician named Dinic nearly simultaneously, and independently, developed an O(ev^2) algorithm which we can see beats Edmonds-karp as edge density grows.

There's no way the general public will think of Richard Karp or Stephen Cook as a hero because they won't even be able to say anything resembling what they did.

> Karp wrote that all of her friends are using Instagram and Snapchat, Well...

Edmonds-karp was developed (really just a modified Ford-Faulkerson approach with a BFS as opposed to a random augmenting path...but we'll give it to him), yielding an O(ve^2) algorithm.

So we should recall the nice Karp result in about 1972: With meager assumptions on the probability distribution of the cities, for any number x, no matter how small, as the number of cities n goes to infinity, there is a simple approach that will come within x% of optimality with probability 1 - x.

The Railgun implementation seems to be a combination of improved Boyer-Moore (Boyer-Moore-Horspool-Sunday) with Rabin-Karp (which uses hashing).

But Karp's approach also works the same in R^m for any positive integer m.

You can just use the characterization of NP in terms of certificates and deterministic verifying machines, and still get everything (except maybe the standard proof of the Karp-Lipton theorem).