Letteratura scientifica selezionata sul tema "Random weighted graphs"
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Articoli di riviste sul tema "Random weighted graphs"
Komjáthy, Júlia, e Bas Lodewijks. "Explosion in weighted hyperbolic random graphs and geometric inhomogeneous random graphs". Stochastic Processes and their Applications 130, n. 3 (marzo 2020): 1309–67. http://dx.doi.org/10.1016/j.spa.2019.04.014.
Testo completoVengerovsky, V. "Eigenvalue Distribution of Bipartite Large Weighted Random Graphs. Resolvent Approach". Zurnal matematiceskoj fiziki, analiza, geometrii 12, n. 1 (25 marzo 2016): 78–93. http://dx.doi.org/10.15407/mag12.01.078.
Testo completoDavis, Michael, Zhanyu Ma, Weiru Liu, Paul Miller, Ruth Hunter e Frank Kee. "Generating Realistic Labelled, Weighted Random Graphs". Algorithms 8, n. 4 (8 dicembre 2015): 1143–74. http://dx.doi.org/10.3390/a8041143.
Testo completoAmini, Hamed, Moez Draief e Marc Lelarge. "Flooding in Weighted Sparse Random Graphs". SIAM Journal on Discrete Mathematics 27, n. 1 (gennaio 2013): 1–26. http://dx.doi.org/10.1137/120865021.
Testo completoAmini, Hamed, e Marc Lelarge. "The diameter of weighted random graphs". Annals of Applied Probability 25, n. 3 (giugno 2015): 1686–727. http://dx.doi.org/10.1214/14-aap1034.
Testo completoGanesan, Ghurumuruhan. "Weighted Eulerian extensions of random graphs". Gulf Journal of Mathematics 16, n. 2 (12 aprile 2024): 1–11. http://dx.doi.org/10.56947/gjom.v16i2.1866.
Testo completoPorfiri, Maurizio, e Daniel J. Stilwell. "Consensus Seeking Over Random Weighted Directed Graphs". IEEE Transactions on Automatic Control 52, n. 9 (settembre 2007): 1767–73. http://dx.doi.org/10.1109/tac.2007.904603.
Testo completoKhorunzhy, O., M. Shcherbina e V. Vengerovsky. "Eigenvalue distribution of large weighted random graphs". Journal of Mathematical Physics 45, n. 4 (aprile 2004): 1648–72. http://dx.doi.org/10.1063/1.1667610.
Testo completoMountford, Thomas, e Jacques Saliba. "Flooding and diameter in general weighted random graphs". Journal of Applied Probability 57, n. 3 (settembre 2020): 956–80. http://dx.doi.org/10.1017/jpr.2020.45.
Testo completoMosbah, M., e N. Saheb. "Non-uniform random spanning trees on weighted graphs". Theoretical Computer Science 218, n. 2 (maggio 1999): 263–71. http://dx.doi.org/10.1016/s0304-3975(98)00325-9.
Testo completoTesi sul tema "Random weighted graphs"
Davidson, Angus William. "Scaling properties of optimisation problems on random weighted graphs". Thesis, University of Bristol, 2018. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.752771.
Testo completoGabrysch, Katja. "On Directed Random Graphs and Greedy Walks on Point Processes". Doctoral thesis, Uppsala universitet, Analys och sannolikhetsteori, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-305859.
Testo completoRuss, Ricardo. "Service Level Achievments - Test Data for Optimal Service Selection". Thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-50538.
Testo completoWeibel, Julien. "Graphons de probabilités, limites de graphes pondérés aléatoires et chaînes de Markov branchantes cachées". Electronic Thesis or Diss., Orléans, 2024. http://www.theses.fr/2024ORLE1031.
Testo completoGraphs are mathematical objects used to model all kinds of networks, such as electrical networks, communication networks, and social networks. Formally, a graph consists of a set of vertices and a set of edges connecting pairs of vertices. The vertices represent, for example, individuals, while the edges represent the interactions between these individuals. In the case of a weighted graph, each edge has a weight or a decoration that can model a distance, an interaction intensity, or a resistance. Modeling real-world networks often involves large graphs with a large number of vertices and edges.The first part of this thesis is dedicated to introducing and studying the properties of the limit objects of large weighted graphs : probability-graphons. These objects are a generalization of graphons introduced and studied by Lovász and his co-authors in the case of unweighted graphs. Starting from a distance that induces the weak topology on measures, we define a cut distance on probability-graphons. We exhibit a tightness criterion for probability-graphons related to relative compactness in the cut distance. Finally, we prove that this topology coincides with the topology induced by the convergence in distribution of the sampled subgraphs. In the second part of this thesis, we focus on hidden Markov models indexed by trees. We show the strong consistency and asymptotic normality of the maximum likelihood estimator for these models under standard assumptions. We prove an ergodic theorem for branching Markov chains indexed by trees with general shapes. Finally, we show that for a stationary and reversible chain, the line graph is the tree shape that induces the minimal variance for the empirical mean estimator among trees with a given number of vertices
Caetano, Tiberio Silva. "Graphical models and point set matching". reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2004. http://hdl.handle.net/10183/4041.
Testo completoPoint pattern matching in Euclidean Spaces is one of the fundamental problems in Pattern Recognition, having applications ranging from Computer Vision to Computational Chemistry. Whenever two complex patterns are encoded by two sets of points identifying their key features, their comparison can be seen as a point pattern matching problem. This work proposes a single approach to both exact and inexact point set matching in Euclidean Spaces of arbitrary dimension. In the case of exact matching, it is assured to find an optimal solution. For inexact matching (when noise is involved), experimental results confirm the validity of the approach. We start by regarding point pattern matching as a weighted graph matching problem. We then formulate the weighted graph matching problem as one of Bayesian inference in a probabilistic graphical model. By exploiting the existence of fundamental constraints in patterns embedded in Euclidean Spaces, we prove that for exact point set matching a simple graphical model is equivalent to the full model. It is possible to show that exact probabilistic inference in this simple model has polynomial time complexity with respect to the number of elements in the patterns to be matched. This gives rise to a technique that for exact matching provably finds a global optimum in polynomial time for any dimensionality of the underlying Euclidean Space. Computational experiments comparing this technique with well-known probabilistic relaxation labeling show significant performance improvement for inexact matching. The proposed approach is significantly more robust under augmentation of the sizes of the involved patterns. In the absence of noise, the results are always perfect.
Weihrauch, Tobias. "Characterizations and Probabilistic Representations of Effective Resistance Metrics". 2019. https://ul.qucosa.de/id/qucosa%3A73920.
Testo completoLibri sul tema "Random weighted graphs"
Coolen, A. C. C., A. Annibale e E. S. Roberts. Specific constructions. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.003.0009.
Testo completoCoolen, A. C. C., A. Annibale e E. S. Roberts. Random graph ensembles. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.003.0003.
Testo completoNewman, Mark. Mathematics of networks. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198805090.003.0006.
Testo completoCapitoli di libri sul tema "Random weighted graphs"
Walley, Scott K., e Harry H. Tan. "Shortest paths in random weighted graphs". In Lecture Notes in Computer Science, 213–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/bfb0030835.
Testo completoBroise-Alamichel, Anne, Jouni Parkkonen e Frédéric Paulin. "Random Walks on Weighted Graphs of Groups". In Equidistribution and Counting Under Equilibrium States in Negative Curvature and Trees, 141–54. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-18315-8_6.
Testo completoKumagai, Takashi. "Heat Kernel Estimates for Random Weighted Graphs". In Lecture Notes in Mathematics, 59–64. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-03152-1_5.
Testo completoDai, Qionghai, e Yue Gao. "Mathematical Foundations of Hypergraph". In Artificial Intelligence: Foundations, Theory, and Algorithms, 19–40. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0185-2_2.
Testo completoDani, Varsha, e Cristopher Moore. "Independent Sets in Random Graphs from the Weighted Second Moment Method". In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, 472–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22935-0_40.
Testo completoNalam, Chaitanya, e Thatchaphol Saranurak. "Maximal k-Edge-Connected Subgraphs in Weighted Graphs via Local Random Contraction". In Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 183–211. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2023. http://dx.doi.org/10.1137/1.9781611977554.ch8.
Testo completoGamarnik, David, Tomasz Nowicki e Grzegorz Swirszcz. "Maximum Weight Independent Sets and Matchings in Sparse Random Graphs". In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, 357–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-27821-4_32.
Testo completoAckermann, Hanno, Björn Scheuermann, Tat-Jun Chin e Bodo Rosenhahn. "Randomly Walking Can Get You Lost: Graph Segmentation with Unknown Edge Weights". In Lecture Notes in Computer Science, 450–63. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14612-6_33.
Testo completoGimadi, E. Kh. "Several Edge-Disjoint Spanning Trees with Given Diameter in a Graph with Random Discrete Edge Weights". In Communications in Computer and Information Science, 281–92. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-48751-4_21.
Testo completoGimadi, Edward Kh, Aleksandr S. Shevyakov e Alexandr A. Shtepa. "On Asymptotically Optimal Approach for the Problem of Finding Several Edge-Disjoint Spanning Trees of Given Diameter in an Undirected Graph with Random Edge Weights". In Mathematical Optimization Theory and Operations Research, 67–78. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77876-7_5.
Testo completoAtti di convegni sul tema "Random weighted graphs"
Oren-Loberman, Mor, Vered Paslev e Wasim Huleihel. "Testing Dependency of Weighted Random Graphs". In 2024 IEEE International Symposium on Information Theory (ISIT), 1263–68. IEEE, 2024. http://dx.doi.org/10.1109/isit57864.2024.10619266.
Testo completoAmini, Hamed, Moez Draief e Marc Lelarge. "Flooding in Weighted Random Graphs". In 2011 Proceedings of the Eighth Workshop on Analytic Algorithmics and Combinatorics (ANALCO). Philadelphia, PA: Society for Industrial and Applied Mathematics, 2011. http://dx.doi.org/10.1137/1.9781611973013.1.
Testo completoHero III, Alfred O., e Olivier Michel. "Robust entropy estimation strategies based on edge weighted random graphs". In SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, a cura di Ali Mohammad-Djafari. SPIE, 1998. http://dx.doi.org/10.1117/12.323804.
Testo completoCoppersmith, D., P. Doyle, P. Raghavan e M. Snir. "Random walks on weighted graphs, and applications to on-line algorithms". In the twenty-second annual ACM symposium. New York, New York, USA: ACM Press, 1990. http://dx.doi.org/10.1145/100216.100266.
Testo completoLarroca, Federico, Paola Bermolen, Marcelo Fiori e Gonzalo Mateos. "Change Point Detection in Weighted and Directed Random Dot Product Graphs". In 2021 29th European Signal Processing Conference (EUSIPCO). IEEE, 2021. http://dx.doi.org/10.23919/eusipco54536.2021.9616036.
Testo completoKalisky, Tomer. "Scale-Free properties of weighted random graphs: Minimum Spanning Trees and Percolation". In SCIENCE OF COMPLEX NETWORKS: From Biology to the Internet and WWW: CNET 2004. AIP, 2005. http://dx.doi.org/10.1063/1.1985379.
Testo completoCui, Yaxin, Faez Ahmed, Zhenghui Sha, Lijun Wang, Yan Fu e Wei Chen. "A Weighted Network Modeling Approach for Analyzing Product Competition". In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22591.
Testo completoCai, Shaowei, Wenying Hou, Jinkun Lin e Yuanjie Li. "Improving Local Search for Minimum Weight Vertex Cover by Dynamic Strategies". In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/196.
Testo completoDoshi, Vishwaraj, Jie Hu e Do Young Eun. "Self-Repellent Random Walks on General Graphs - Achieving Minimal Sampling Variance via Nonlinear Markov Chains (Extended Abstract)". In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. California: International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/929.
Testo completoXinyi Chen. "Priority weighted BA random graph model". In 2011 International Conference on Computer Science and Service System (CSSS). IEEE, 2011. http://dx.doi.org/10.1109/csss.2011.5972129.
Testo completoRapporti di organizzazioni sul tema "Random weighted graphs"
Goetsch, Arthur L., Yoav Aharoni, Arieh Brosh, Ryszard (Richard) Puchala, Terry A. Gipson, Zalman Henkin, Eugene D. Ungar e Amit Dolev. Energy Expenditure for Activity in Free Ranging Ruminants: A Nutritional Frontier. United States Department of Agriculture, giugno 2009. http://dx.doi.org/10.32747/2009.7696529.bard.
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