  We tackle the problem of estimating a regression function observed in an
instrumental regression framework. This model is an inverse problem with
unknown operator. We provide a spectral cut-off estimation procedure which
enables to derive oracle inequalities which warrants that our estimate, built
without any prior knowledge, behaves as well as, up to $\log$ term, if the best
model were known.
