In high dimensional data, the general performance of traditional clustering algorithms decreases. This is partly because the similarity criterion used by these algorithms becomes ...
In high-dimensional query processing, the optimization of the logical page-size of index structures is an important research issue. Even very simple query processing techniques suc...
We introduce a framework for defining a distance on the (non-Euclidean) space of Linear Dynamical Systems (LDSs). The proposed distance is induced by the action of the group of o...
This paper introduces a new approach to constructing meaningful lower dimensional representations of sets of data points. We argue that constraining the mapping between the high a...
Subspace clustering has attracted great attention due to its capability of finding salient patterns in high dimensional data. Order preserving subspace clusters have been proven to...