In this article, we show several results obtained by combining the use of stable distributions with pseudorandom generators for bounded space. In particular: —We show that, for a...
High dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Recent research results indicate that in high dimension...
This paper presents a generalized approach for performing general rotations in the n-Dimensional Euclidean space around any arbitrary (n-2)-Dimensional subspace. It first shows th...
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
Graph pyramids are often used for representing irregular image pyramids. For the 2D case, combinatorial pyramids have been recently defined in order to explicitly represent more ...