A even cheaper trick
	• Suppose we completely ignore the prior over weight vectors – This is equivalent to giving all possible weight vectors the same prior probability density. • Then all we have to do is to maximize: • This is called maximum likelihood learning. It is very widely used for fitting models in statistics.