Here is a common problem: you have some machine learning algorithm you want to use but it has these damn hyperparameters. These are numbers like weight decay magnitude, Gaussian kernel width, and so forth. The algorithm doesn’t set them, instead, it’s up to you to determine their values. If you don’t set these parameters to “good” values the algorithm doesn’t work. So what do you do?

However, if you want to use LIPO in practice there are some issues that need to be addressed.

source: L