David wrote:

> It’s also some results that John could use at NIPS as a baseline for “standard ML techniques” to compare Ludescher et al against.

Yes, I support this project and I'll be glad to help!

My recent post in [El Niño project - thinking about the next steps](http://forum.azimuthproject.org/discussion/1382/el-nino-project-thinking-about-the-next-steps/?Focus=12497#Comment_12497) was part of my plan to avoid complete embarrassment or nerve-racking suspense by making sure that without much new effort I can put together some reasonable talk at NIPS. But this sounds like a great extra initiative.

Maybe I can use my (limited) skill in climate science to help you prepare a very specific coding challenge for Dara. First, a basic question. When you talk about

> predicting the El Nino 3.4 index (or some variant) using:

> * Linear regression, linear regression with $L_2$ prior, linear regression with $L_1$ prior, linear regression with $L_{1/2}$ prior.

> * Bilinear regression, bilinear regression with $L_2$ prior, bilinear regression with $L_1$ prior, bilinear regression with $L_{1/2}$ prior.

are you talking about predicting the El Niño 3.4 index at some time given just previous values of this index, or - more demanding but potentially much more rewarding - given previous values of the temperature at a grid of points in the Pacific. The latter is the sort of data that Ludescher _et al_ use, so it could help "benchmark" their program.