  We present a novel approach for learning nonlinear dynamic models, which
leads to a new set of tools capable of solving problems that are otherwise
difficult. We provide theory showing this new approach is consistent for models
with long range structure, and apply the approach to motion capture and
high-dimensional video data, yielding results superior to standard
alternatives.
