To address the of mining a huge volume of geographically distributed databases, we propose two approaches. The first one is to download only a sample of each database. The second ...
Abstract. In this paper we present a novel analysis of a random sampling approach for three clustering problems in metric spaces: k-median, min-sum kclustering, and balanced k-medi...
We derive the limiting form of the eigenvalue spectrum for sample covariance matrices produced from non-isotropic data. For the analysis of standard PCA we study the case where th...
The aim of this paper is to compare Bayesian network classifiers to the k-NN classifier based on a subset of features. This subset is established by means of sequential feature se...
- In the general case of non-uniformly spaced frequency domain data and/or arbitrarily colored disturbing noise, the frequency domain subspace identification algorithms described i...