We consider the problem of maintaining frequency counts for items occurring frequently in the union of multiple distributed data streams. Na?ive methods of combining approximate f...
Amit Manjhi, Vladislav Shkapenyuk, Kedar Dhamdhere...
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
Many datasets can be described in the form of graphs or networks where nodes in the graph represent entities and edges represent relationships between pairs of entities. A common ...
Event detection is a critical task in sensor networks, especially for environmental monitoring applications. Traditional solutions to event detection are based on analyzing one-sh...
In this paper a novel clustering algorithm is proposed, namely Variational Multilevel Mesh Clustering (VMLC). The algorithm incorporates the advantages of both hierarchical and va...