I have created a live demo of MOE on a Terminal.com snapshot. More details here:

https://atharwat.wordpress.com/2014/07/27/moe-on-terminal-co...

Neat!

For those interested in this sort of thing, a couple of other libraries with a similar range of uses:

https://github.com/hyperopt/hyperopt https://github.com/JasperSnoek/spearmint

Would be interested if anyone has any thoughts on how these compare (I've been quite impressed so far by hyperopt but haven't tried the others yet).

There are a variety of different techniques that solve similar problems. We have some of them documented here: http://yelp.github.io/MOE/why_moe.html#other-methods (including these two), but would love to add more.

Each one has different tradeoffs depending on what your problem entails, what license you can use and what platform you are running on. Many of these methods have been around for some time. The seminal paper was published in 1998: http://www.ressources-actuarielles.net/EXT/ISFA/1226.nsf/0/f...

MOE provides many interfaces (REST, Python, C++), a permissive license (Apache v2) and allows for many optimal points to be quickly queried at once, non-sequentially (Expected Parallel Improvement), along with a slew of other features. We have also tried to follow strict software engineering principles throughout (testing, docing, etc). We are always looking to improve though and are taking pull requests and suggestions for improvements! https://github.com/Yelp/MOE/issues

Multi Armed Bandit Power for Continuous Spaces!