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In this paper, we consider distributed linear least squares (LLS) and Bayesian minimum mean square error (BMMSE) parameter estimation over sensor networks. In particular, we propose distributed iterative algorithms that asymptotically converge to the centralized solutions. These algorithms are first studied for the case of unclustered (flat architecture) sensor networks; in this venue, we provide...
We propose a new cluster validity index. A data partition is described by a set of disjoint sub-graphs, each corresponding to the minimum spanning tree of a cluster, taking as edge weight the dissimilarity between linked objects. Based on the assumption that each cluster has a characteristic parametric distribution of dissimilarity increments, graph probabilities are estimated. The validity index...
Probabilistic data have recently become popular in applications such as scientific and geospatial databases. For images and other spatial datasets, probabilistic values can capture the uncertainty in extent and class of the objects in the images. Relating one such dataset to another by spatial joins is an important operation for data management systems. We consider probabilistic spatial join (PSJ)...
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