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Optimising the cost function

After defining the model and finding a way to evaluate the cost
function, the next problem is to optimise the cost function. This
will be done in a way that is very similar to the EM algorithm, i.e.
by updating one part of the model at a time while keeping all the
other parameters fixed. All the optimisation steps aim at finding a
minimum of the cost function with the current values for fixed
parameters. Since all the steps decrease the value of the cost
function, the learning algorithm is guaranteed to converge.

**Subsections**

Antti Honkela
2001-05-30