3 citations · 5 across the 6 of their papers we have counts for
3 papers · 1 filter
GreediRIS: Scalable Influence Maximization using Distributed Streaming Maximum Cover
Reet Barik, Wade Cappa, S M Ferdous +3
Influence maximization--the problem of identifying a subset of k influential seeds (vertices) in a network--is a classical problem in network science with numerous applications. Th…
Fused Breadth-First Probabilistic Traversals on Distributed GPU Systems
Reece Neff, Mostafa Eghbali Zarch, Marco Minutoli +4
Probabilistic breadth-first traversals (BPTs) are used in many network science and graph machine learning applications. In this paper, we are motivated by the application of BPTs i…
HBMax: Optimizing Memory Efficiency for Parallel Influence Maximization on Multicore Architectures
Xinyu Chen, Marco Minutoli, Jiannan Tian +3
Influence maximization aims to select k most-influential vertices or seeds in a network, where influence is defined by a given diffusion process. Although computing optimal seed se…