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.

Data, data, data...

Bing! That's data. Data, data, data.

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?

Say sorted data is data.

little data, old data, no data. So back in 1995,

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

Data

Data...

Data

Data

Data

Data

like DNA data or brain data.

Raw data now! Raw data now!

looking at wind data and solar data.

We could talk about government data, enterprise data is really important, there's scientific data, there's personal data, there's weather data, there's data about events, there's data about talks, and there's news and there's all kinds of stuff.

Data Viewer

(binary data)

raw data

? target data?

Merge data

Data Mode

Data mode

Data size

Data encoding

Data Section

Data Project

Text Data

Data DVD

Data CD

Data Disk

Preparing data

ISO9660 data

Writing data

Data Protection

Data Directory

Move Data