Academic literature on the topic 'Hypergraph Models'

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Journal articles on the topic "Hypergraph Models"

1

Luqman, Anam, Muhammad Akram, and Ali N. A. Koam. "Granulation of Hypernetwork Models under the q-Rung Picture Fuzzy Environment." Mathematics 7, no. 6 (2019): 496. http://dx.doi.org/10.3390/math7060496.

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In this paper, we define q-rung picture fuzzy hypergraphs and illustrate the formation of granular structures using q-rung picture fuzzy hypergraphs and level hypergraphs. Further, we define the q-rung picture fuzzy equivalence relation and q-rung picture fuzzy hierarchical quotient space structures. In particular, a q-rung picture fuzzy hypergraph and hypergraph combine a set of granules, and a hierarchical structure is formed corresponding to the series of hypergraphs. The mappings between the q-rung picture fuzzy hypergraphs depict the relationships among granules occurring at different levels. The consequences reveal that the representation of the partition of the universal set is more efficient through q-rung picture fuzzy hypergraphs and the q-rung picture fuzzy equivalence relation. We also present an arithmetic example and comparison analysis to signify the superiority and validity of our proposed model.
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Robeva, Elina, and Anna Seigal. "Duality of graphical models and tensor networks." Information and Inference: A Journal of the IMA 8, no. 2 (2018): 273–88. http://dx.doi.org/10.1093/imaiai/iay009.

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Abstract In this article we show the duality between tensor networks and undirected graphical models with discrete variables. We study tensor networks on hypergraphs, which we call tensor hypernetworks. We show that the tensor hypernetwork on a hypergraph exactly corresponds to the graphical model given by the dual hypergraph. We translate various notions under duality. For example, marginalization in a graphical model is dual to contraction in the tensor network. Algorithms also translate under duality. We show that belief propagation corresponds to a known algorithm for tensor network contraction. This article is a reminder that the research areas of graphical models and tensor networks can benefit from interaction.
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DeFranco, Mario DeFranco, and Paul E. Gunnells. "Hypergraph Matrix Models." Moscow Mathematical Journal 21, no. 4 (2021): 737–66. http://dx.doi.org/10.17323/1609-4514-2021-21-4-737-766.

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GROSS, ELIZABETH, and SONJA PETROVIĆ. "COMBINATORIAL DEGREE BOUND FOR TORIC IDEALS OF HYPERGRAPHS." International Journal of Algebra and Computation 23, no. 06 (2013): 1503–20. http://dx.doi.org/10.1142/s0218196713500331.

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Associated to any hypergraph is a toric ideal encoding the algebraic relations among its edges. We study these ideals and the combinatorics of their minimal generators, and derive general degree bounds for both uniform and non-uniform hypergraphs in terms of balanced hypergraph bicolorings, separators, and splitting sets. In turn, this provides complexity bounds for algebraic statistical models associated to hypergraphs. As two main applications, we recover a well-known complexity result for Markov bases of arbitrary 3-way tables, and we show that the defining ideal of the tangential variety is generated by quadratics and cubics in cumulant coordinates.
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Hao, Yong-Jing, Ying-Lian Gao, Mi-Xiao Hou, Ling-Yun Dai, and Jin-Xing Liu. "Hypergraph Regularized Discriminative Nonnegative Matrix Factorization on Sample Classification and Co-Differentially Expressed Gene Selection." Complexity 2019 (August 19, 2019): 1–12. http://dx.doi.org/10.1155/2019/7081674.

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Nonnegative Matrix Factorization (NMF) is a significant big data analysis technique. However, standard NMF regularized by simple graph does not have discriminative function, and traditional graph models cannot accurately reflect the problem of multigeometry information between data. To solve the above problem, this paper proposed a new method called Hypergraph Regularized Discriminative Nonnegative Matrix Factorization (HDNMF), which captures intrinsic geometry by constructing hypergraphs rather than simple graphs. The introduction of the hypergraph method allows high-order relationships between samples to be considered, and the introduction of label information enables the method to have discriminative effect. Both the hypergraph Laplace and the discriminative label information are utilized together to learn the projection matrix in the standard method. In addition, we offered a corresponding multiplication update solution for the optimization. Experiments indicate that the method proposed is more effective by comparing with the earlier methods.
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GUNATILLEKA, DANUL K. "COUNTABLE MODELS OF THE THEORIES OF BALDWIN–SHI HYPERGRAPHS AND THEIR REGULAR TYPES." Journal of Symbolic Logic 84, no. 3 (2019): 1007–19. http://dx.doi.org/10.1017/jsl.2019.28.

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AbstractWe continue the study of the theories of Baldwin–Shi hypergraphs from [5]. Restricting our attention to when the rank δ is rational valued, we show that each countable model of the theory of a given Baldwin–Shi hypergraph is isomorphic to a generic structure built from some suitable subclass of the original class used in the construction. We introduce a notion of dimension for a model and show that there is a an elementary chain $\left\{ {\mathfrak{M}_\beta :\beta \leqslant \omega } \right\}$ of countable models of the theory of a fixed Baldwin–Shi hypergraph with $\mathfrak{M}_\beta \preccurlyeq \mathfrak{M}_\gamma $ if and only if the dimension of $\mathfrak{M}_\beta $ is at most the dimension of $\mathfrak{M}_\gamma $ and that each countable model is isomorphic to some $\mathfrak{M}_\beta $. We also study the regular types that appear in these theories and show that the dimension of a model is determined by a particular regular type. Further, drawing on a large body of work, we use these structures to give an example of a pseudofinite, ω-stable theory with a nonlocally modular regular type, answering a question of Pillay in [11].
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Mikov, A. I., and A. A. Mikov. "Connectivity and routes in large geometric network hypergraphs." Informatization and communication, no. 2 (February 16, 2021): 76–80. http://dx.doi.org/10.34219/2078-8320-2021-12-2-76-80.

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Random geometric hypergraphs are considered as mathematical models of large wireless computer networks. The dependences of the mathematical expectation of the number of hyper-edges in random geometric hypergraphs on the radii of reliable reception / transmission of radio signals by network nodes, as well as on the number of vertices in the hyper- graph are studied. The concepts of the shortest route in a geometric hypergraph are discussed. Calculations of the probabil- ity of connectivity of large random geometric hypergraphs, the mathematical expectation of the diameter of hypergraphs and its change with a change in the radii of the nodes are carried out. The presentation of the results is accompanied by graphs.
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8

Laguna, Miguel, José Marqués, and Guillermo Rodríguez-Cano. "Feature diagram formalization based on directed hypergraphs." Computer Science and Information Systems 8, no. 3 (2011): 611–33. http://dx.doi.org/10.2298/csis100804016l.

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Feature models are used to represent the variability and commonality of software product lines (SPL), and to decide on the configuration of specific applications. Several variants based on tree or graph hierarchical structures have been proposed. These structures are completed with additional constraints, generally expressed in parallel with the feature diagram. This paper proposes the use of hypergraphs to integrate both concepts in a unique characterization. Therefore, the definition, validation and selection of feature configurations can be internally based on the hypergraph properties and well-known algorithms, while the concrete visual syntax remains unchanged for domain engineers. The implemented hypergraph algorithms have been tested using a complete set of feature diagrams. Finally a feature meta-model can be derived directly from the formal definitions, providing the foundations for building feature modeling tools.
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9

Owrang O., M. M. "Query Translation Based on Hypergraph Models." Computer Journal 31, no. 2 (1988): 155–64. http://dx.doi.org/10.1093/comjnl/31.2.155.

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10

Chung, Fan, and Alexander Tsiatas. "Hypergraph Coloring Games and Voter Models." Internet Mathematics 10, no. 1-2 (2014): 66–86. http://dx.doi.org/10.1080/15427951.2013.833676.

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