Outlier or anomaly detection is an important task in data analysis. We discuss the problem from a geometrical perspective and provide framework which exploits metric structure of set. Our approach rests on manifold assumption, that is, observed, nominally high-dimensional lie much lower dimensional this intrinsic can be inferred with learning methods. show exploiting significantly improves outl...