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Publications [#264711] of Guillermo Sapiro

Papers Published

  1. Tepper, M; Sapiro, G, All for one, one for all: Consensus community detection in networks, 2015 Ieee International Conference on Acoustics, Speech, and Signal Processing (Icassp) (January, 2014), pp. 1075-1079, IEEE, ISSN 1520-6149 [doi]
    (last updated on 2019/07/19)

    Given an universe of distinct, low-level communities of a network, we aim at identifying the 'meaningful' and consistent communities in this universe. We address this as the process of obtaining consensual community detections and formalize it as a bi-clustering problem. While most consensus algorithms only take into account pairwise relations and end up analyzing a huge matrix, our proposed characterization of the consensus problem (1) does not drop useful information, and (2) analyzes a much smaller matrix, rendering the problem tractable for large networks. We also propose a new pa-rameterless bi-clustering algorithm, fit for the type of matrices we analyze. The approach has proven successful in a very diverse set of experiments, ranging from unifying the results of multiple community detection algorithms to finding common communities from multi-modal or noisy networks. © 2014 IEEE.
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