In this paper we propose a novel clustering algorithm based on maximizing the mutual information between data points and clusters. Unlike previous methods, we neither assume the d...
We show in this note that by deterministic packet sampling, the tail of the distribution of the original flow size can be obtained by rescaling that of the sampled flow size. To re...
In this paper, we present a complete computational pipeline for extracting a compact shape descriptor for curve point cloud data. Our shape descriptor, called a barcode, is based ...
Anne D. Collins, Afra Zomorodian, Gunnar Carlsson,...
A neural network with fixed topology can be regarded as a parametrization of functions, which decides on the correlations between functional variations when parameters are adapted...
Abstract. Five methods for count data clusterization based on Poisson mixture models are described. Two of them are parametric, the others are semi-parametric. The methods emlploy ...