: Kernel density estimation for multivariate data is an important technique that has a wide range of applications. However, it has received significantly less attention than its un...
Similarity search and data mining often rely on distance or similarity functions in order to provide meaningful results and semantically meaningful patterns. However, standard dist...
Tobias Emrich, Franz Graf, Hans-Peter Kriegel, Mat...
— In order to reduce the computational load of the recursive least squares (RLS) algorithm, a decomposition based least squares algorithm is developed for non-uniformly sampled m...
: This article provides a comparison among different methods for estimating the aggregation of Internet traffic resulting from different users, network-access types and correspondi...
Over the past few years, some embedding methods have been proposed for feature extraction and dimensionality reduction in various machine learning and pattern classification tasks...