Results 11 to 20 of about 248,790 (377)
Balancing minimum spanning trees and shortest-path trees [PDF]
Algorithmica, 1995 This paper give a simple linear-time algorithm that, given a weighted digraph, finds a spanning tree that simultaneously approximates a shortest-path tree and a minimum spanning tree. The algorithm provides a continuous trade-off: given the two trees and epsilon > 0, the algorithm returns a spanning tree in which the distance between any vertex and ...
Khuller, S, Raghavachari, B, Young, N
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On the Length of a Random Minimum Spanning Tree [PDF]
Combinatorics, Probability and Computing, 2015 We study the expected value of the lengthLnof the minimum spanning tree of the complete graphKnwhen each edgeeis given an independent uniform [0, 1] edge weight. We sharpen the result of Frieze [6] that limn→∞$\mathbb{E}$(Ln) = ζ(3) and show that$$ \mathbb{E}(L_n)=\zeta(3)+\frac{c_1}{n}+\frac{c_2+o(1)}{n^{4/3}}, $$wherec1,c2are explicitly defined ...
COOPER, COLIN +4 more
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Involve, a Journal of Mathematics, 2009 The minimum spanning tree problem originated in the 1920s when O. Borůvka identified and solved the problem during the electrification of Moravia. This graph theory problem and its numerous applications have inspired many others to look for alternate ways of finding a spanning tree of minimum weight in a weighted, connected graph since Borůvka’s time ...
Jayawant, Pallavi, Glavin, Kerry
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Some models for inverse minimum spanning tree problem with uncertain edge weights [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2022 The inverse minimum spanning tree (IMST) problem is an inverse optimization problem in which one makes the least modification to the edge weights of a predetermined spanning tree, to make it the minimum spanning tree with respect to new edge weights ...
Sagarika Biswal, Ganesh Ghorai
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Successive minimum spanning trees [PDF]
Random Structures & Algorithms, 2021 AbstractIn a complete graphwith independent uniform(or exponential) edge weights, letbe the minimum‐weight spanning tree (MST), andthe MST after deleting the edges of all previous trees. We show that each tree's weightconverges in probability to a constant, with, and we conjecture that.
Janson, Svante, Sorkin, Gregory B.
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Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering [PDF]
SIGMOD Conference, 2021 This paper presents new parallel algorithms for generating Euclidean minimum spanning trees and spatial clustering hierarchies (known as HDBSCAN*).
Yiqiu Wang +3 more
semanticscholar +1 more source
Cosmology and neutrino mass with the Minimum Spanning Tree [PDF]
Monthly notices of the Royal Astronomical Society, 2021 The information content of the minimum spanning tree (MST), used to capture higher-order statistics and information from the cosmic web, is compared to that of the power spectrum for a νΛCDM model.
K. Naidoo, E. Massara, O. Lahav
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A sharp threshold for minimum bounded-depth and bounded-diameter spanning trees and Steiner trees in random networks [PDF]
, 2012 In the complete graph on n vertices, when each edge has a weight which is an exponential random variable, Frieze proved that the minimum spanning tree has weight tending to zeta(3)=1/1^3+1/2^3+1/3^3+... as n goes to infinity.
Omer Angel +2 more
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Data‐driven performance metrics for neural network learning
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri +2 more
wiley +1 more source
Evolutionary diversity optimization and the minimum spanning tree problem [PDF]
Annual Conference on Genetic and Evolutionary Computation, 2020 In the area of evolutionary computation the calculation of diverse sets of high-quality solutions to a given optimization problem has gained momentum in recent years under the term evolutionary diversity optimization.
Jakob Bossek, F. Neumann
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