is use a maximum a posteriori estimate which is which means that we're going to approximate this integral with just a point estimate for theta star where theta star is whatever actually maximizes the log probability of theta given D meta train which again is a very standard thing to do in machine learning so this Arg max that I have written on the right side here this is the meta learning problem the meta learning problem is to pull out the right theta from your meta training data so that that theta contains everything you need