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Accelerating the mining of influential nodes in complex networks through community detection., , and . Conf. Computing Frontiers, page 64-71. ACM, (2016)Tolerating correlated failures for generalized Cartesian distributions via bipartite matching., , , and . Conf. Computing Frontiers, page 36. ACM, (2011)Guest Editorial: Advances in Parallel Graph Processing: Algorithms, Architectures, and Application Frameworks., and . IEEE Trans. Multi Scale Comput. Syst., 4 (3): 188-189 (2018)HBMax: Optimizing Memory Efficiency for Parallel Influence Maximization on Multicore Architectures., , , , , and . PACT, page 412-425. ACM, (2022)Algorithms for Vertex-Weighted Matching in Graphs.. Old Dominion University, Norfolk, Virginia, USA, (2009)base-search.net (ftolddominionuni:oai:digitalcommons.odu.edu:computerscience_etds-1057).Security in Distributed Digital Libraries: Issues and Challenges ., , and . ICPP Workshops, page 480-486. IEEE Computer Society, (2002)Optimizing Approximate Weighted Matching on Nvidia Kepler K40., , , , and . HiPC, page 105-114. IEEE Computer Society, (2015)MiniVite: A Graph Analytics Benchmarking Tool for Massively Parallel Systems., , , , and . PMBS@SC, page 51-56. IEEE, (2018)Influence Maximization on Complex Networks with Intrinsic Nodal Activation., and . SocInfo (2), volume 10047 of Lecture Notes in Computer Science, page 133-141. (2016)On the Impact of Execution Models: A Case Study in Computational Chemistry., , , , , and . IPDPS Workshops, page 255-264. IEEE Computer Society, (2015)