Fast Discrete Distribution Clustering Using Wasserstein Barycenter with Sparse Support
Fast Discrete Distribution Clustering Using Wasserstein Barycenter with Sparse Support
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Ye, Jianbo , Wu, Panruo , Wang, James Z and Li, Jia
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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In a variety of research areas, the weighted bag of vectors and the histogram are widely used descriptors for complex objects. Both can be expressed as discrete distributions. D2-clustering pursues the minimum total within-cluster variation for a set of discrete distributions subject to the Kantorovich-Wasserstein metric. D2-clustering has a severe...
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Fast Discrete Distribution Clustering Using Wasserstein Barycenter with Sparse Support
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TN_cdi_proquest_journals_2075329744
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2075329744
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2331-8422
