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Covariance sketching has been recently introduced as an effective strategy to reduce the data dimensionality without sacrificing the ability to reconstruct second-order statistics of the data. In this paper, we propose a novel covariance sketching scheme with reduced complexity for spatial-temporal data, whose covariance matrices satisfy the Kronecker product expansion model recently introduced by...
Graph clustering, where the goal is to cluster the nodes in a graph into disjoint clusters, arises from applications such as community detection, network monitoring, and bioinformatics. This paper describes an approach for graph clustering based on a small number of linear measurements, i.e. sketches, of the adjacency matrix, where each sketch corresponds to the number of edges in a randomly selected...
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