High-dimensional problems arising from robot motion planning, biology, data mining, and geographic information systems often require the computation of k nearest neighbor (knn) gr...
Clustering algorithms play an important role in data analysis and information retrieval. How to obtain a clustering for a large set of highdimensional data suitable for database ap...
Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This p...
— Log-linear models are widely used for labeling feature vectors and graphical models, typically to estimate robust conditional distributions in presence of a large number of pot...
In this paper a novel and generic approach for model-based data clustering in a boosting framework is presented. This method uses the forward stagewise additive modeling to learn t...