I'm partitioning a partitioned unit.

This is called fuel partitioning in the lingo.

Spectral partitioning, L1 minimization. This comes from the optimization community.

It's sort of cool that Top K via partitioning as just described works.

The time it takes to run Top K via partitioning on one element.

It's kind of a partially sorted list, and we call this partitioning around V.

So, lets imagine there is some problem called graph partitioning which is a real problem.

Now, the partitioning algorithm is going to split this list L into a left and a right.

Do we know that graph partitioning is in NP, and therefore an exponential time solution would exist?

Let's go over now how we can actually solve the top K problem using this idea of partitioning.

Back set! Front set!

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When we observe the world, what we're doing is we're taking the current belief state and partitioning it up into pieces.

Right. Let's do an analysis of the time it takes for a Top K to do its work via this partitioning approach.

This is very similar to the K partitioning algorithm from the lectures, but returns a single value only, instead of a list.

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