Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
This paper deals with the on-line allocation of shared data objects to the local memory modules of the nodes in a network. We assume that the data is organized in indivisible objec...
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...
t ion which is much more abstract than a place vocabulary, the kinematic topology. Kinematic topology does not define qualitative inference rules, but provides a characterization o...
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...