Dimension reduction and manifold learning play an important role in robotics, multimedia processing and data mining. For these tasks strong methods like Unsupervised Kernel Regression [4, 7] or Gaussian Process Latent Variable Models [5, 6] have been proposed in the last years. But many methods suffer from numerous local optima and crucial parameter dependencies. We use advanced methods from st...
