—The Possibilistic Latent Variable (PLV) clustering algorithm is a powerful tool for the analysis of complex datasets due to its robustness toward data distributions of different...
In this paper, we develop a new language construct to address one of the pitfalls of parallel programming: precise handling of events across parallel components. The construct, te...
William Thies, Michal Karczmarek, Janis Sermulins,...
We argue that K–means and deterministic annealing algorithms for geometric clustering can be derived from the more general Information Bottleneck approach. If we cluster the ide...
We consider the problem of semantic load shedding for continuous queries containing window joins on multiple data streams and propose a robust approach that is effective with the ...
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...