In my last post, where I wrote about sequential parameter optimization, I asked you if you did some assumptions about the underlying function when trying to find the optimal spot. (If you missed this and you’re interested in an easy introduction to sequential parameter optimization you might like to have a look here.)
But back to the assumptions. If you don’t want to do a random search, you definitely take some assumptions about the underlying function. That might be something simple, like ‘following the steepest path leads to the highest spot’ or more complex assumptions about the nature of the function, like ‘it might be polynomial’.
The former assumption can be used for a simple search strategy, the latter for building a surrogate model that hopefully resembles the function. Continue reading
hands on
Explaining sequential parameter optimization
When asked what I’m working on, I’m always having some difficulties to explain it. Where to start explaining? How far to go into detail? And how to explain at all without pen and paper??
But it’s an exciting area of research and actually not that complicated. So I had the idea to develop this little game. Continue reading