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Influence maximization is the problem of finding a small set of most influential nodes in a social network so that their aggregated influence in the network is maximized. In this paper, we study influence maximization in the linear threshold model, one of the important models formalizing the behavior of influence propagation in social networks. We first show that computing exact influence in general...
In the unstructured P2P networks, the flooding resource search method may cause much communication overhead, and severely constrains the scalability of network. In order to overcome this disadvantage, a new search strategy named TTL-Search based on the local caching and the scope of searching requests is proposed in this paper. According to this strategy, the searching process is divided into two...
Simulating a lively forest in real time is a challenging problem due to the high complexities in both scene geometry and dynamic effects. In this paper, we introduce a novel hybrid model to efficiently synthesize realistic swaying effects of trees under winds. An approximate lighting algorithm is also proposed to render realistic lakes. Our method effectively takes advantage of the horse power of...
In this paper, an approach is presented to compute the efficient frontier for portfolio optimization based on particle swarm optimization (PSO). A generalization of the standard Markowitz mean-variance model which includes transaction costs and floor and ceiling constraints is considered. Due to these complex practical constrains exact algorithms fail to work efficiently, so the use of heuristic algorithms...
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