Multiple Passes of FM
In most practical applications, FM is run multiple times with the Best-of-N wrapper.
Question: Can the current run be improved by considering previous runs? (i.e. learning)
We have gathered initial data and there appears to be good opportunity to cut many runs short in later runs, and thus double the speed of Best-of-N FM.