We present a new Bi-level LSH algorithm to perform approximate k-nearest neighbor search in high dimensional spaces. Our formulation is based on a two-level scheme. In the first ...
We give a tutorial overview of several geometric methods for dimension reduction. We divide the methods into projective methods and methods that model the manifold on which the da...
We give a bound on the expected reconstruction error for a general coding method where data in a Hilbert space are represented by finite dimensional coding vectors. The result can...
Abstract. We describe an algorithm called TargetCluster for the discretization of continuous targets in subgroup discovery. The algorithm identifies patterns in the target data an...
We present a new unsupervised learning technique for the discovery of temporal clusters in large data sets. Our method performs hierarchical decomposition of the data to find stru...