AUTHOR=Jung Alexander TITLE=On the Complexity of Sparse Label Propagation JOURNAL=Frontiers in Applied Mathematics and Statistics VOLUME=4 YEAR=2018 URL=https://www.frontiersin.org/journals/applied-mathematics-and-statistics/articles/10.3389/fams.2018.00022 DOI=10.3389/fams.2018.00022 ISSN=2297-4687 ABSTRACT=

This paper investigates the computational complexity of sparse label propagation which has been proposed recently for processing network-structured data. Sparse label propagation amounts to a convex optimization problem and might be considered as an extension of basis pursuit from sparse vectors to clustered graph signals representing the label information contained in network-structured datasets. Using a standard first-order oracle model, we characterize the number of iterations for sparse label propagation to achieve a prescribed accuracy. In particular, we derive an upper bound on the number of iterations required to achieve a certain accuracy and show that this upper bound is sharp for datasets having a chain structure (e.g., time series).