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BS 2583-1955 Specification for podger spanners.pdf
- BS 2583-1955 Specification for podger spanners
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Mining Structural Hole Spanners Through Information Diffusion in Social Networks.pdf
- Mining Structural Hole Spanners Through Information Diffusion in Social NetworksMining Structural Hole Spanners Through Information Diffusion in Social NetworksMining Structural Hole Spanners Through Information Diffusion in Social Networks
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parabolic yao-type geometric spanners in wireless ad hoc networks.pdf
- parabolic yao-type geometric spanners in wireless ad hoc networks
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Beyond Boundary Spanners The:超越边界扳手.pdf
- Beyond Boundary Spanners The：超越边界扳手超越边界,超越边界,The,the
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Mining Structural Hole Spanners in Social Networks.pdf
- Mining Structural Hole Spanners in Social Networks
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Constant Density Spanners for Wireless Ad hoc Networks.ppt
- Constant Density Spanners for Wireless Ad hoc Networks
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Constant Density Spanners for Wireless Ad hoc Networks.pptx
- Constant Density Spanners for Wireless Ad hoc Networks
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Shallow, Low, and Light Trees, and Tight Lower Bounds for Euclidean Spanners.pdf
- euclidean euclidean distance euclidean距离 non euclidean setbounds euclidean norm euclidean space bounds boundschecker injustdecodebounds
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A Simple and Linear Time Randomized Algorithm for Computing Sparse Spanners in Weighted Graphs.pdf
- Let G = (V, E) be an undirected weighted graph on |V | = n vertices, and |E| = m edges. A t-spanner of the graph G, for any t 1, is a subgraph (V, ES), ES E, such that the distance between any pair of vertices in the subgraph is at most t times the distance between them in the graph G. Computing a t-spanner of minimum size (number of edges) has been a widely studied and well motivated problem in computer science. In this paper we present the rst linear time randomized algorithm that computes a t-spanner of a given weighted graph. Moreover, the size of the t-spanner computed essentially matches the worst case lower bound implied by a 43 years old girth conjecture made independently by Erdos [26], Bollob as [19], and Bondy & Simonovits [21]. Our algorithm uses a novel clustering approach that avoids any distance computation altogether. This feature is somewhat surprising since all the previously existing algorithms employ computation of some sort of local or global distance information
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向豆丁求助：有没有Spanners?
