Abstract:We propose a distributionally robust model for the influence maximization problem. Unlike the classic independent cascade model (Kempe et al., 2003), this model's diffusion process is adversarially adapted to the choice of seed set. Hence, instead of optimizing under the assumption that all influence relationships in the network are independent, we seek a seed set whose expected influence under the worst correlation, i.e. the "worst-case, expected influence", is maximized. We show that this worst-case influenc… Show more
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