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Thus, the three representative clusters do not intersect.
Membership degrees of countries are again high, implying representative clusters.
ESC automatically selects representative clusters that will be used to train Gaussian distributions.
This scenario forms an unbiased training feature space containing all possible instances with balanced density between the representative clusters.
After appropriate automatic selection of the representative clusters, the final step is to train a Gaussian distribution per cluster using the Expectation Maximization (EM) algorithm.
First, we create a set of unique input fingerprints by filtering duplicates that are then stored and finally remapped onto their representative clusters.
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A three-dimensional reconstruction of one representative cluster is shown in Figure 2a.
Afterwards, GMMSE constructs a graph based on the new data samples and the representative matrix, and searches for the most representative cluster structure.
In the current typical algorithms for clustering routing, the LEACH (Low-Energy Adaptive Clustering Hierarchy) proposed by [9] is one of the most representative clustering algorithms.
For a subset of faces (n≈250k), we used sparse dictionary learning [40] to find k=300 representative cluster centers and assigned each face to one of the centers.
It relies on a multicast-based listen/announce protocol to monitor state within clusters and uses a tree of point-to-point connections amongst representative cluster nodes to federate clusters and aggregate their state.
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