Abstract Clustering text data streams is an important issue in data mining community and has a number of applications such as news group filtering, text crawling, document organiza...
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
We introduce a new inference algorithm for Dirichlet process mixture models. While Gibbs sampling and variational methods focus on local moves, the new algorithm makes more global...
Clusters of workstations have emerged as a costeffective solution to high performance computing problem. To take advantage of any opportunities, however, effective scheduling tech...
We present a novel approach for adaptively grouping and subdividing hair using discrete level-of-detail (LOD) representations. The set of discrete LODs include hair strands, clust...