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Abstract:
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In recent years network data have become common place in numerous areas such as economics, epidemiology, genomics and sociology. However in a number of significant applications the underlying nodal data are not time series but point processes e.g. neural coding, high frequency finance, genomics. We describe our recent work in this area based on sparsity methods and illustrate with a number of applications including high frequency finance.
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