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Relevant bibliographies by topics / Unlabelled trees

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Journal articles
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Academic literature on the topic 'Unlabelled trees'

Author: Grafiati

Published: 17 July 2021

Last updated: 1 February 2022

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Journal articles on the topic "Unlabelled trees"

1

Jin, Emma Yu, and Benedikt Stufler. "Graph limits of random unlabelled k-trees." Combinatorics, Probability and Computing 29, no. 5 (2020): 722–46. http://dx.doi.org/10.1017/s0963548320000164.

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AbstractWe study random unlabelled k-trees by combining the colouring approach by Gainer-Dewar and Gessel (2014) with the cycle-pointing method by Bodirsky, Fusy, Kang and Vigerske (2011). Our main applications are Gromov–Hausdorff–Prokhorov and Benjamini–Schramm limits that describe their asymptotic geometric shape on a global and local scale as the number of (k + 1)-cliques tends to infinity.

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Gittenberger, Bernhard, Zbigniew Gołębiewski, Isabella Larcher, and Małgorzata Sulkowska. "Protection numbers in simply generated trees and Pólya trees." Applicable Analysis and Discrete Mathematics, no. 00 (2021): 10. http://dx.doi.org/10.2298/aadm190329010g.

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We determine the limit of the expected value and the variance of the protection number of the root in simply generated trees, in P?lya trees, and in unlabelled non-plane binary trees, when the number of vertices tends to infinity. Moreover, we compute expectation and variance of the protection number of a randomly chosen vertex in all those tree classes. We obtain exact formulas as sum representations, where the obtained sums are rapidly converging thus allowing an efficient numerical computation of high accuracy.

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Labelle, Gilbert, Cédric Lamathe, and Pierre Leroux. "Labelled and unlabelled enumeration of k-gonal 2-trees." Journal of Combinatorial Theory, Series A 106, no. 2 (2004): 193–219. http://dx.doi.org/10.1016/j.jcta.2004.01.009.

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Brown, Paul, and Trevor Fenner. "Fast Generation of Unlabelled Free Trees using Weight Sequences." Journal of Graph Algorithms and Applications 25, no. 1 (2021): 219–40. http://dx.doi.org/10.7155/jgaa.00556.

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Panholzer, Alois, and Helmut Prodinger. "Bijections between certain families of labelled and unlabelled d-ary trees." Applicable Analysis and Discrete Mathematics 3, no. 1 (2009): 123–36. http://dx.doi.org/10.2298/aadm0901123p.

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We present enumeration results for d-ary trees whose vertices are coloured by k colours in a specific way. Besides generating functions proofs of these results we also give direct bijections between these coloured trees and uncoloured d-ary trees.

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Goldberg, Leslie Ann, and Mark Jerrum. "Counting Unlabelled Subtrees of a Tree is #P-complete." LMS Journal of Computation and Mathematics 3 (2000): 117–24. http://dx.doi.org/10.1112/s1461157000000243.

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AbstractThe problem of counting unlabelled subtrees of a tree (that is, sub-trees that are distinct up to isomorphism) is #P-complete, and hence equivalent in computational difficulty to evaluating the permanent of a 0,1-matrix.

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CHYZAK, FRÉDÉRIC, MICHAEL DRMOTA, THOMAS KLAUSNER, and GERARD KOK. "The Distribution of Patterns in Random Trees." Combinatorics, Probability and Computing 17, no. 1 (2008): 21–59. http://dx.doi.org/10.1017/s0963548307008425.

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Let $\Tn{}$ denote the set of unrooted labelled trees of size n and let ℳ be a particular (finite, unlabelled) tree. Assuming that every tree of $\Tn{}$ is equally likely, it is shown that the limiting distribution as n goes to infinity of the number of occurrences of ℳ is asymptotically normal with mean value and variance asymptotically equivalent to μn and σ2n, respectively, where the constants μ>0 and σ≥0 are computable.

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Pavlov, Yu L. "Limit theorems on sizes of trees in a random unlabelled forest." Discrete Mathematics and Applications 15, no. 2 (2005): 153–70. http://dx.doi.org/10.1515/1569392053971424.

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9

Edwards, Keith. "The Harmonious Chromatic Number of Almost All Trees." Combinatorics, Probability and Computing 4, no. 1 (1995): 31–46. http://dx.doi.org/10.1017/s0963548300001462.

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A harmonious colouring of a simple graph G is a proper vertex colouring such that each pair of colours appears together on at most one edge. The harmonious chromatic number h(G) is the least number of colours in such a colouring.For any positive integer m, let Q(m) be the least positive integer k such that ≥ m. We show that for almost all unlabelled, unrooted trees T, h(T) = Q(m), where m is the number of edges of T.

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Flouri, T., K. Kobert, S. P. Pissis, and A. Stamatakis. "An optimal algorithm for computing all subtree repeats in trees." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 372, no. 2016 (2014): 20130140. http://dx.doi.org/10.1098/rsta.2013.0140.

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Given a labelled tree T , our goal is to group repeating subtrees of T into equivalence classes with respect to their topologies and the node labels. We present an explicit, simple and time-optimal algorithm for solving this problem for unrooted unordered labelled trees and show that the running time of our method is linear with respect to the size of T . By unordered, we mean that the order of the adjacent nodes (children/neighbours) of any node of T is irrelevant. An unrooted tree T does not have a node that is designated as root and can also be referred to as an undirected tree. We show how

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Dissertations / Theses on the topic "Unlabelled trees"

1

Pouryahya, Fatemeh. "Small Peripheral Structures in Unlabelled Trees and the Evolution of Polyploids." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42413.

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Many angiosperms have undergone some series of polyploidization events over the course of their evolutionary history. In these genomes, especially those resulting from multiple autopolyploidization, it may be relatively easy to recognize all the sets of n homeologous chromosomes, but it is much harder, if not impossible, to partition these chromosomes into n subgenomes, each representing one distinct genomic component of chromosomes making up the original polyploid. Thus, if we wish to infer the polyploidization history of the genome, we could make use of all the gene trees inferred from

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Book chapters on the topic "Unlabelled trees"

1

Micheli, Anne, and Dominique Rossin. "Edit Distance between Unlabelled Ordered Trees." In Mathematics and Computer Science III. Birkhäuser Basel, 2004. http://dx.doi.org/10.1007/978-3-0348-7915-6_26.

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Ohkura, Nobuhito, Kouichi Hirata, Tetsuji Kuboyama, and Masateru Harao. "The q-Gram Distance for Ordered Unlabeled Trees." In Discovery Science. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11563983_17.

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3

Borisova, I. A., and N. G. Zagoruiko. "Algorithm FRiS-TDR for Generalized Classification of the Labeled, Semi-labeled and Unlabeled Datasets." In Clusters, Orders, and Trees: Methods and Applications. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0742-7_9.

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Xiang, Yang, Zoe Jingyu Zhu, and Yu Li. "Enumerating Unlabeled and Root Labeled Trees for Causal Model Acquisition." In Advances in Artificial Intelligence. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01818-3_17.

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Suzuki, Yusuke, Takayoshi Shoudai, Satoshi Matsumoto, and Tomoyuki Uchida. "Efficient Learning of Unlabeled Term Trees with Contractible Variables from Positive Data." In Inductive Logic Programming. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39917-9_23.

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"Complements on Unlabeled Enumeration." In Combinatorial Species and Tree-like Structures. Cambridge University Press, 1997. http://dx.doi.org/10.1017/cbo9781107325913.006.

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Monikandan, Sivaramakrishnan. "Reconstruction of Graphs." In Graph Theory [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.98726.

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A graph is reconstructible if it is determined up to isomorphism from the collection of all its one-vertex deleted unlabeled subgraphs. One of the foremost unsolved problems in Graph Theory is the Reconstruction Conjecture, which asserts that every graph G on at least three vertices is reconstructible. In 1980’s, tremendous work was done and many significant results have been produced on the problem and its variations. During the last three decades, work on it has slowed down gradually. P. J. Kelly (1957) first noted that trees are reconstructible; but the proof is quite lengthy. A short proof, due to Greenwell and Hemminger (1973), was given which is based on a simple, but powerful, counting theorem. This chapter deals with the counting theorem and its subsequent applications; also it ends up with a reduction of the Reconstruction Conjecture using distance and connectedness, which may lead to the final solution of the conjecture.

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Conference papers on the topic "Unlabelled trees"

1

Bifet, Albert, and Ricard Gavaldà. "Mining adaptively frequent closed unlabeled rooted trees in data streams." In the 14th ACM SIGKDD international conference. ACM Press, 2008. http://dx.doi.org/10.1145/1401890.1401900.

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Zhang, Teng, and Zhi-Hua Zhou. "Semi-Supervised Optimal Margin Distribution Machines." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/431.

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Semi-supervised support vector machines is an extension of standard support vector machines with unlabeled instances, and the goal is to find a label assignment of the unlabeled instances, so that the decision boundary has the maximal \textit{minimum margin} on both the original labeled instances and unlabeled instances. Recent studies, however, disclosed that maximizing the minimum margin does not necessarily lead to better performance, and instead, it is crucial to optimize the \textit{margin distribution}. In this paper, we propose a novel approach SODM (Semi-supervised Optimal margin Distr

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3

Sankarpandi, Sathish K., Spyros Samothrakis, Luca Citi, and Peter Brady. "Active learning without unlabeled samples: generating questions and labels using Monte Carlo Tree Search." In 2019 IEEE International Conference on Big Data (Big Data). IEEE, 2019. http://dx.doi.org/10.1109/bigdata47090.2019.9006276.

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Oliveira, Elias, Howard Roatti, Matheus de Araujo Nogueira, Henrique Gomes Basoni, and Patrick Marques Ciarelli. "Using the Cluster-based Tree Structure of k-Nearest Neighbor to Reduce the Effort Required to Classify Unlabeled Large Datasets." In Special Session on Text Mining. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005615305670576.

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