We propose simple and fast methods based on nearest neighbors that order objects from high-dimensional data sets from typical points to untypical points. On the one hand, we show ...
Stefan Harmeling, Guido Dornhege, David M. J. Tax,...
Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional ...
: Single training image face recognition is one of main challenges to appearance-based pattern recognition techniques. Many classical dimensionality reduction methods such as LDA h...