Training a function that maps n-dim to n-dim
I would call a mapping between N dimensional input and N dimensional output a regression problem. 

If you add more constraints about the relation between the input and output it might be called different names: linear filtering, nonlinear filtering, etc...

some examples on common techniques for that would be: neural networks, regression trees, regularised regressions...