An important class of heuristics for constraint satisfaction problems works by sampling information during search in order to inform subsequent decisions. One of these strategies, ...
A nonparametric Bayesian model for histogram clustering is proposed to automatically determine the number of segments when Markov Random Field constraints enforce smooth class assi...
We present a probabilistic model for clustering of objects represented via pairwise dissimilarities. We propose that even if an underlying vectorial representation exists, it is b...
Julia E. Vogt, Sandhya Prabhakaran, Thomas J. Fuch...
Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clust...
Complex virtual environments can be simulated with physical or procedural motion. Physical motion is more realistic, but requires the integration of an ordinary differential equat...