Relevant bibliographies by topics / Tree graphs

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Tree graphs'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 February 2022

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Journal articles on the topic "Tree graphs"

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Mandal, Subhrangsu, and Arobinda Gupta. "Convergecast Tree on Temporal Graphs." International Journal of Foundations of Computer Science 31, no. 03 (April 2020): 385–409. http://dx.doi.org/10.1142/s012905412050015x.

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Temporal graphs are useful tools to model dynamic network topologies found in many applications. In this paper, we address the problem of constructing a convergecast tree on temporal graphs for data collection in dynamic sensor networks. Two types of convergecast trees, bounded arrival time convergecast tree and minimum total arrival time convergecast tree are defined as useful structures for low delay data collection. An [Formula: see text] time centralized algorithm is proposed to construct a bounded arrival time convergecast tree, where [Formula: see text] is the number of nodes, [Formula: see text] is the number of edges, and [Formula: see text] is the lifetime of the given temporal graph. The algorithm presented is an offline algorithm and assumes that all information about change in the graph topology is known apriori. It is then shown that the problem of constructing a minimum total arrival time convergecast tree is NP-complete, and an [Formula: see text] time centralized, offline heuristic algorithm is proposed to address it. The heuristic algorithm is evaluated with experiments on four real life data sets.
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Guo, Haiyan, and Bo Zhou. "On the α-spectral radius of graphs." Applicable Analysis and Discrete Mathematics, no. 00 (2020): 22. http://dx.doi.org/10.2298/aadm180210022g.

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For 0 ? ? ? 1, Nikiforov proposed to study the spectral properties of the family of matrices A?(G) = ?D(G)+(1 ? ?)A(G) of a graph G, where D(G) is the degree diagonal matrix and A(G) is the adjacency matrix of G. The ?-spectral radius of G is the largest eigenvalue of A?(G). For a graph with two pendant paths at a vertex or at two adjacent vertices, we prove results concerning the behavior of the ?-spectral radius under relocation of a pendant edge in a pendant path. We give upper bounds for the ?-spectral radius for unicyclic graphs G with maximum degree ? ? 2, connected irregular graphs with given maximum degree and some other graph parameters, and graphs with given domination number, respectively. We determine the unique tree with the second largest ?-spectral radius among trees, and the unique tree with the largest ?-spectral radius among trees with given diameter. We also determine the unique graphs so that the difference between the maximum degree and the ?-spectral radius is maximum among trees, unicyclic graphs and non-bipartite graphs, respectively.
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Hao, Long. "A Novel Algorithm Based on the Degree Tree for Graph Isomorphism." Advanced Materials Research 225-226 (April 2011): 417–21. http://dx.doi.org/10.4028/www.scientific.net/amr.225-226.417.

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The graph isomorphism problem is to study the relationship between two graphs which seem to be different, but essentially identically. A novel algorithm based on the degree tree is proposed, where each node of the tree describes a given vertex and its neighboring information of a graph. Two vertexes in different graphs are regarded as mapping if the corresponding nodes and all their junior nodes are similar. Hence by comparing their degree trees, two graphs can be determined whether matching or not, and the mapping vertexes can be found. Experimental results show the approach’s performance.
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Bunke, H., and B. T. Messmer. "Recent Advances in Graph Matching." International Journal of Pattern Recognition and Artificial Intelligence 11, no. 01 (February 1997): 169–203. http://dx.doi.org/10.1142/s0218001497000081.

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A powerful and universal data structure with applications invarious subfields of science and engineering is graphs. In computer vision and image analysis, graphs are often used for the representation of structured objects. For example, if the problem is to recognize instances of known objects in an image, then often models, or prototypes, of the known objects are represented by means of graphs and stored in a database. The unknown objects in the input image are extracted by means of suitable preprocessing and segmentation algorithms, and represented by graphs that are analogous to the model graphs. Thus, the problem of object recognition is transformed into a graph matching problem. In this paper, it is assumed that there is an input graph that is given on-line, and a number of model, or prototype, graphs that are known a priori. We present a new approach to subgraph isomorphism detection which is based on a compact representation of the model graphs that is computed off-line. Subgraphs that appear multiple times within the same or within different model graphs are represented only once, thus reducing the computational effort to detect them in an input graph. In the extreme case where all model graphs are highly similar, the run time of the new algorithm becomes independent of the number of model graphs. We also describe an extension of this method to error-correcting graph matching. Furthermore, an approach to subgraph isomorphism detection based on decision trees is proposed. A decision tree is generated from the models in an off-line phase. This decision tree can be used for subgraph isomorphism detection. The time needed for decision tree traversal is only polynomial in terms of the number of nodes of the input graph. Moreover, the time complexity of the decision tree traversal is completely independent on the number of model graphs, regardless of their similarity. However, the size of the decision tree is exponential in the number of nodes of the models. To cut down the space complexity of the decision tree, some pruning strategies are discussed.
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Smirnov, Alexander Valeryevich. "NP-completeness of the Minimum Spanning Tree Problem of a Multiple Graph of Multiplicity k ≥ 3." Modeling and Analysis of Information Systems 28, no. 1 (March 24, 2021): 22–37. http://dx.doi.org/10.18255/1818-1015-2021-1-22-37.

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In this paper, we study undirected multiple graphs of any natural multiplicity k > 1. There are edges of three types: ordinary edges, multiple edges and multi-edges. Each edge of the last two types is a union of k linked edges, which connect 2 or (k + 1) vertices correspondingly. The linked edges should be used simultaneously. If a vertex is incident to a multiple edge, it can be also incident to other multiple edges and it can be the common end of k linked edges of some multi-edge. If a vertex is the common end of some multi-edge, it cannot be the common end of another multi-edge. A multiple tree is a connected multiple graph with no cycles. Unlike ordinary trees, the number of edges in a multiple tree is not fixed. The problem of finding the spanning tree can be set for a multiple graph. Complete spanning trees form a special class of spanning trees of a multiple graph. Their peculiarity is that a multiple path joining any two selected vertices exists in the tree if and only if such a path exists in the initial graph. If the multiple graph is weighted, the minimum spanning tree problem and the minimum complete spanning tree problem can be set. Also we can formulate the problems of recognition of the spanning tree and complete spanning tree of the limited weight. The main result of this article is the proof of NPcompleteness of such recognition problems for arbitrary multiple graphs as well as for divisible multiple graphs in the case when multiplicity k ≥ 3. The corresponding optimization problems are NP-hard.
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BHABAK, PUSPAL, and HOVHANNES A. HARUTYUNYAN. "Approximation Algorithm for the Broadcast Time in k-Path Graph." Journal of Interconnection Networks 19, no. 04 (December 2019): 1950006. http://dx.doi.org/10.1142/s0219265919500063.

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Broadcasting is an information dissemination problem in a connected network in which one node, called the originator, must distribute a message to all other nodes by placing a series of calls along the communication lines of the network. In every unit of time, the informed nodes aid the originator in distributing the message. Finding the broadcast time of any vertex in an arbitrary graph is NP-complete. The polynomial time solvability is shown only for certain graphs like trees, unicyclic graphs, tree of cycles, necklace graphs, fully connected trees and tree of cliques. In this paper we study the broadcast problem in k-path graphs. For any originator of the k-path graph we present a (4 – ϵ)-approximation algorithm in the worst case. The algorithm gives a better approximation ratio for some large classes of k-path graphs. Moreover, our algorithm generates the optimal broadcast time for some cases.
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LYONS, RUSSELL. "Identities and Inequalities for Tree Entropy." Combinatorics, Probability and Computing 19, no. 2 (December 15, 2009): 303–13. http://dx.doi.org/10.1017/s0963548309990605.

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The notion of tree entropy was introduced by the author as a normalized limit of the number of spanning trees in finite graphs, but is defined on random infinite rooted graphs. We give some new expressions for tree entropy; one uses Fuglede–Kadison determinants, while another uses effective resistance. We use the latter to prove that tree entropy respects stochastic domination. We also prove that tree entropy is non-negative in the unweighted case, a special case of which establishes Lück's Determinant Conjecture for Cayley-graph Laplacians. We use techniques from the theory of operators affiliated to von Neumann algebras.
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Thenge, J. D., B. Surendranath Reddy, and Rupali S. Jain. "Contribution to Soft Graph and Soft Tree." New Mathematics and Natural Computation 15, no. 01 (December 25, 2018): 129–43. http://dx.doi.org/10.1142/s179300571950008x.

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Soft set theory introduced by D. Molodstov is a new theory which deals with uncertainty. Connected graphs can be represented by using soft sets called soft graphs. In the present paper, we introduce the tabular representation of soft graph and define radius, diameter, center and degree of soft graph. We also define union, product of soft graphs and soft trees. We then derive some properties of radius, degree of vertex in soft graph and soft trees.
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Maksimov, Anatoliy G., Arsenii D. Zavalishin, Maxim V. Abramov, and Alexander L. Tulupyev. "Adjacency Tree Families and Complementarity Criteria." Computer tools in education, no. 1 (March 30, 2020): 28–37. http://dx.doi.org/10.32603/2071-2340-2020-1-28-37.

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The article is aimed at generalizing the concepts of a derivative graph and a primitive graph for graphs with trunk connectivity. Theorems are formulated and proved on the main connectedness of the graph of the derivative and on the graph of the antiderivative main connected graphs. The theoretical and practical significance lies in the study of structures that will be best suited for working with algebraic Bayesian networks and, thus, become one of the goal of their machine learning. We note the novelty of looking at the problem, or rather, studying the question for which families of graphs there is a set of loads, the family of MGS over which exactly coincides with the given one.
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Smirnov, Alexander V. "The Spanning Tree of a Divisible Multiple Graph." Modeling and Analysis of Information Systems 25, no. 4 (August 27, 2018): 388–401. http://dx.doi.org/10.18255/1818-1015-2018-4-388-401.

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In this paper, we study undirected multiple graphs of any natural multiplicity k > 1. There are edges of three types: ordinary edges, multiple edges and multi-edges. Each edge of the last two types is a union of k linked edges, which connect 2 or k + 1 vertices, correspondingly. The linked edges should be used simultaneously. If a vertex is incident to a multiple edge, it can be also incident to other multiple edges, and it can be the common ending vertex to k linked edges of a multi-edge. If a vertex is the common end of some multi-edge, it cannot be the common end of any other multi-edge. Special attention is paid to the class of divisible multiple graphs. The main peculiarity of them is a possibility to divide the graph into k parts, which are adjusted on the linked edges and which have no common edges. Each part is an ordinary graph. The definition of a multiple tree is stated and the basic properties of such trees are studied. Unlike ordinary trees, the number of edges in a multiple tree is not fixed. In the article, the evaluation of the minimum and maximum number of edges in the divisible tree is stated and proved. Next, the definitions of the spanning tree and the complete spanning tree of a multiple graph are given. The criterion of completeness of the spanning tree is proved for divisible graphs. It is also proved that a complete spanning tree exists in any divisible graph. If the multiple graph is weighted, the minimum spanning tree problem and the minimum complete spanning tree problem can be set. In the article, we suggest a heuristic algorithm for the minimum complete spanning tree problem for a divisible graph.
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Dissertations / Theses on the topic "Tree graphs"

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Mahoney, James Raymond. "Tree Graphs and Orthogonal Spanning Tree Decompositions." PDXScholar, 2016. http://pdxscholar.library.pdx.edu/open_access_etds/2944.

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Given a graph G, we construct T(G), called the tree graph of G. The vertices of T(G) are the spanning trees of G, with edges between vertices when their respective spanning trees differ only by a single edge. In this paper we detail many new results concerning tree graphs, involving topics such as clique decomposition, planarity, and automorphism groups. We also investigate and present a number of new results on orthogonal tree decompositions of complete graphs.
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Abu-Ata, Muad Mustafa. "Tree-Like Structure in Graphs and Embedability to Trees." Kent State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=kent1397345185.

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Besomi, Ormazábal Guido Andrés. "Tree embeddings in dense graphs." Tesis, Universidad de Chile, 2018. http://repositorio.uchile.cl/handle/2250/164009.

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Magíster en Ciencias de la Ingeniería, Mención Matemáticas Aplicadas
Memoria para optar al título de Ingeniero Civil Matemático
En 1995 Komlós, Sárközy y Szemerédi probaron que para cualquier $\delta>0$ y cualquier entero positivo $\Delta$, todo grafo $G$ de orden $n$, con $n$ suficientemente grande, que satisfaga $\delta(G)\geq (1+\delta)\frac{n}{2}$, contiene como subgrafo a todo árbol de $n$ vértices y grado máximo acotado por $\Delta$. En esta memoria se presentan dos posibles generalizaciones de este resultado, estableciendo condiciones suficientes para el \textit{embedding} de árboles de orden $k$ en grafos con grado mínimo al menos $(1+\delta)\frac{k}{2}$, donde $k$ es lineal en el orden del grafo anfitrión. En 1963 Erd\H{o}s y Sós conjeturaron que, dado un entero $k$, un grafo $G$ con grado promedio mayor que $k-1$ debería contener todos los árboles en $k$ aristas como subgrafos. Como consecuencia de uno de los resultados principales de esta memoria, se demuestra una versión parcial de la conjetura de Erd\H{o}s-Sós. Siguiendo la linea del \textit{embedding} de árboles en grafos con condiciones de grado mínimo, Havet, Reed, Stein y Wood conjeturaron el 2016 que todo grafo con grado mínimo al menos $\lfloor\frac{2k}{3}\rfloor$ y grado máximo al menos $k$ contiene todo árbol con $k$ aristas como subgrafo. Las técnicas aquí desarrolladas permiten, adicionalmente, probar una versión parcial de esta conjetura.
CMM - Conicyt PIA AFB170001
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Naveed, Ahmed Azam. "On Enumeration of Tree-Like Graphs and Pairwise Compatibility Graphs." Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/263783.

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Tarrés, Puertas Marta Isabel. "Direct tree decomposition of geometric constraint graphs." Doctoral thesis, Universitat Politècnica de Catalunya, 2014. http://hdl.handle.net/10803/285011.

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The evolution of constraint based geometric models is tightly tied to parametric and feature-based Computer-Aided Design (CAD) systems. Since the introduction of parametric design by Pro/Engineer in the 1980's, most major CAD systems adopted constraint based geometric models as a core technology. Constraint based geometric models allowed CAD systems to provide a more powerful data model while offering an intuitive user interface. Later on, the same models also found application to fields like linkage design, chemical modeling, computer vision and dynamic geometry. Constraint based geometric models are unevaluated models. A key problem related to constraint based geometric models is the geometric constraint based solving problem which, roughly speaking, can be stated as the problem of evaluating a constraint based model. Among the different approaches to geometric constraint solving, we are interested in graph-based Decomposition-Recombination solvers. In the graph-based constructive approach, the geometric problem is first translated into a graph whose vertices represent the set of geometric elements and whose edges are the constraints. Then the constraint problem is solved by decomposing the graph into a set of sub-problems, each sub-problem is recursively divided until reaching basic problems which are solved by a dedicated equational solver. The solution to the initial problem is computed by merging the solutions to the sub-problems. The approach used by DR-solvers has been particularly successful when the decomposition into subproblems and subsequent recombination of solutions to these subproblems can be described by a plan generated a priori, that is, a plan generated as a preprocessing step without actually solving the subsystems. The plan output by the DR-planner remains unchanged as numerical values of parameters change. Such a plan is known as a DR-plan and the unit in the solver that generates it is the DR-planner. In this setting, the DR-plan is then used to drive the actual solving process, that is, computing specific coordinates that properly place geometric objects with respect to each other. In this thesis we develop a new DR-planner algorithm for graph-constructive two dimensional DR-solvers. This DR-planner is based on the tree-decomposition of a graph. The triangle- or tree-decomposition of a graph decomposes a graph into three subgraphs such that subgraphs pairwise share one vertex. Shared vertices are called hinges. The tree-decomposition of a geometric constraint graph is in some sense the construction plan that solves the corresponding problem. The DR-planner algorithm first transforms the input graph into a simpler, planar graph. After that, an specific planar embedding is computed for the transformed graph where hinges, if any, can be straightly found. In the work we proof the soundness of the new algorithm. We also show that the worst case time performance of the resthe number of vertices of the input graph. The resulting algorithm is easy to implement and is as efficient as other known solving algorithms.
L'evolució de models geomètrics basats en restriccions està fortament lligada al sistemes de Disseny Assistit per Computador (CAD) paramètrics i als basats en el paradigma de disseny per mitjà de característiques. Des de la introducció del disseny paramètric per part de Pro/Engineer en els anys 80, la major part de sistemes CAD utilitzaren com a tecnologia de base els models geomètrics basats en restriccions. Els models geomètrics basats en restriccions permeteren als sistemes CAD proporcionar un model d'informació més ampli i alhora oferir una interfície d'usuari intuitiva. Posteriorment, els mateixos models s'aplicaren en camps com el disseny de mecanismes, el modelatge químic, la visió per computador i la geometria dinàmica. Els models geomètrics basats en restriccions són models no avaluats. Un problema clau relacionat amb el models de restriccions geomètriques és el problema de la resolució de restriccions geomètriques, que es resumeix com el problema d'avaluar un model basat en restriccions. Entre els diferents enfocs de resolució de restriccions geomètriques, tractem els solvers de Descomposició-Recombinació (DR-solvers) basats en graphs. En l'enfoc constructiu basat en grafs, el problema geomètric es trasllada en un pas inicial a un graf, on els vèrtexs del graf representen el conjunt d'elements geomètrics i on les arestes corresponen a les restriccions geomètriques entre els elements. A continuació el problema de restriccions es resol descomposant el graf en un conjunt de subproblemes, cadascun dels quals es divideix recursivament fins a obtenir problemes bàsics, que sovint són operacions geomètriques realitzables, per exemple, amb regle i compàs, i que es resolen per mitjà d'un solver numèric específic. Finalment, la solució del problema inicial s'obté recombinant les solucions dels subproblemes. L'enfoc utilitzat pels DR-solvers ha esdevingut especialment interessant quan la descomposició en subproblemes i la posterior recombinació de solucions d'aquests subproblemes es pot descriure com un pla de construcció generat a priori, és a dir, un pla generat com a pas de pre-procés sense necessitat de resoldre realment els subsistemes. El pla generat pel DR-planner esdevé inalterable encara que els valors numèrics dels paràmetres canviin. Aquest pla es coneix com a DR-plan i la unitat en el solver que el genera és l'anomenat DR-planner. En aquest context, el DR-plan s'utilitza com a eina del procés de resolució en curs, és a dir, permet calcular les coordenades específiques que correctament posicionen els elements geomètrics uns respecte els altres. En aquesta tesi desenvolupem un nou algoritme que és la base del DR-planner per a DR-solvers constructius basats en grafs en l'espai bidimensional. Aquest DR-planner es basa en la descomposició en arbre d'un graf. La descomposició en triangles o arbre de descomposició d'un graf es basa en descomposar un graf en tres subgrafs tals que comparteixen un vèrtex 2 a 2. El conjunt de vèrtexs compartits s'anomenen \emph{hinges}. La descomposició en arbre d'un graf de restriccions geomètriques equival, en cert sentit, a resoldre el problema de restriccions geomètriques. L'algoritme del DR-planner en primer lloc transforma el graf proporcionat en un graf més simple i planar. A continuació, es calcula el dibuix en el pla del graf transformat, on les hinges, si n'hi ha, es calculen de manera directa. En aquest treball demostrem la correctesa del nou algoritme. Finalment, proporcionem l'estudi de la complexitat temporal de l'algoritme en cas pitjor i demostrem que és quadràtica en el nombre de vèrtexs del graf proporcionat. L'algoritme resultant és senzill d'implementar i tan eficient com altres algoritmes de resolució concrets
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Rhodes, Benjamin Robert. "On the Discrete Number of Tree Graphs." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/98536.

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We study a generalization of the problem of finding bounds on the number of discrete chains, which itself is a generalization of the Erdős unit distance problem. Given a set of points in Euclidean space and a tree graph consisting of a much smaller number of vertices, we study the maximum possible number of tree graphs which can be represented by a prescribed tree graph. We derive an algorithm for finding tight bounds for this family of problems up to chain bound discrepancy, and give upper and lower bounds in special cases.
Master of Science
We study a generalization of the problem of finding bounds on the number of discrete chains, which itself is a generalization of the Erdős unit distance problem, a famous mathematics problem named after mathematician Paul Erdős. Given a set of points, and a tree graph of a much smaller amount of vertices, we study the maximum possible number of tree graphs which can be represented by a prescribed tree graph. We derive an algorithm for finding tight bounds for this family of problems up to chain bound discrepancy, and give upper and lower bounds in special cases.
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Broutin, Nicolas. "Random trees, graphs and recursive partitions." Habilitation à diriger des recherches, Université Pierre et Marie Curie - Paris VI, 2013. http://tel.archives-ouvertes.fr/tel-00842019.

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Je présente dans ce mémoire mes travaux sur les limites d'échelle de grandes structures aléatoires. Il s'agit de décrire les structures combinatoires dans la limite des grandes tailles en prenant un point de vue objectif dans le sens où on cherche des limites des objets, et non pas seulement de paramètres caractéristiques (même si ce n'est pas toujours le cas dans les résultats que je présente). Le cadre général est celui des structures critiques pour lesquelles on a typiquement des distances caractéristiques polynomiales en la taille, et non concentrées. Sauf exception, ces structures ne sont en général pas adaptées aux applications informatiques. Elles sont cependant essentielles de part l'universalité de leurs propriétés asymptotiques, prouvées ou attendues. Je parle en particulier d'arbres uniformément choisis, de graphes aléatoires, d'arbres couvrant minimaux et de partitions récursives de domaines du plan:
Arbres aléatoires uniformes. Il s'agit ici de mieux comprendre un objet limite essentiel, l'arbre continu brownien (CRT). Je présente quelques résultats de convergence pour des modèles combinatoires ''non-branchants'' tels que des arbres sujets aux symétries et les arbres à distribution de degrés fixée. Je décris enfin une nouvelle décomposition du CRT basée sur une destruction partielle.
Graphes aléatoires. J'y décris la construction algorithmique de la limite d'échel-le des graphes aléatoires du modèle d'Erdös--Rényi dans la zone critique, et je fais le lien avec le CRT et donne des constructions de l'espace métrique limite. Arbres couvrant minimaux. J'y montre qu'une connection avec les graphes aléatoires permet de quantifier les distances dans un arbre convrant aléatoire. On obtient non seulement l'ordre de grandeur de l'espérance du diamètre, mais aussi la limite d'échelle en tant qu'espace métrique mesuré. Partitions récursives. Sur deux exemples, les arbres cadrant et les laminations du disque, je montre que des idées basées sur des théorèmes de point fixe conduisent à des convergences de processus, où les limites sont inhabituelles, et caractérisées par des décompositions récursives.
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Leitert, Arne. "Tree-Breadth of Graphs with Variants and Applications." Kent State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=kent1497402176814598.

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Bertacchi, D., and Andreas Cap@esi ac at. "Random Walks on Diestel--Leader Graphs." ESI preprints, 2001. ftp://ftp.esi.ac.at/pub/Preprints/esi1004.ps.

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Sanders, Daniel Preston. "Linear algorithms for graphs of tree-width at most four." Diss., Georgia Institute of Technology, 1993. http://hdl.handle.net/1853/30061.

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Books on the topic "Tree graphs"

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Dror, Moshe. Directed Steiner tree problem on a graph: Models, relaxations, and algorithms. Monterey, Calif: Naval Postgraduate School, 1988.

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Lorca, Xavier. Tree-based Graph Partitioning Constraint. Hoboken, NJ, USA: John Wiley & Sons, Inc, 2011. http://dx.doi.org/10.1002/9781118604304.

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Tree-based graph partitioning constraint. London: ISTE, 2011.

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Irniger, Christophe-André Mario. Graph matching: Filtering databases of graphs using machine learning techniques. Berlin: AKA, 2005.

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Valiente, Gabriel. Algorithms on Trees and Graphs. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002.

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Valiente, Gabriel. Algorithms on Trees and Graphs. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04921-1.

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Gupta, Arvind. Constructivity issues in tree minors. Toronto, Ont: Dept. of Computer Science, University of Toronto, 1990.

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Tree of love. New York: NBM Pub., 2005.

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Reading Graphs, maps & trees: Responses to Franco Moretti. Anderson, SC: Parlor Press, 2011.

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Cai, Jiazhen. Counting embeddings of planar graphs using DFS trees. New York: Courant Institute of Mathematical Sciences, New York University, 1992.

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Book chapters on the topic "Tree graphs"

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Bass, Hyman, and Alexander Lubotzky. "Graphs of Groups and Edge-Indexed Graphs." In Tree Lattices, 17–23. Boston, MA: Birkhäuser Boston, 2001. http://dx.doi.org/10.1007/978-1-4612-2098-5_3.

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Aldous, Joan M., and Robin J. Wilson. "Tree Structures." In Graphs and Applications, 138–62. London: Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0467-4_6.

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Prömel, Hans Jürgen, and Angelika Steger. "Basics I: Graphs." In The Steiner Tree Problem, 1–22. Wiesbaden: Vieweg+Teubner Verlag, 2002. http://dx.doi.org/10.1007/978-3-322-80291-0_1.

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Valiente, Gabriel. "Tree Traversal." In Algorithms on Trees and Graphs, 113–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04921-1_3.

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Valiente, Gabriel. "Tree Isomorphism." In Algorithms on Trees and Graphs, 151–251. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04921-1_4.

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Bruni, Roberto, Ugo Montanari, and Matteo Sammartino. "Algebras for Tree Decomposable Graphs." In Graph Transformation, 203–20. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51372-6_12.

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Fekete, Sándor P., and Jana Kremer. "Tree Spanners in Planar Graphs." In Graph-Theoretic Concepts in Computer Science, 298–309. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/10692760_24.

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Dragan, Feodor F., Chenyu Yan, and Irina Lomonosov. "Collective Tree Spanners of Graphs." In Algorithm Theory - SWAT 2004, 64–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-27810-8_7.

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Abola, Benard, Pitos Seleka Biganda, Christopher Engström, John Magero Mango, Godwin Kakuba, and Sergei Silvestrov. "PageRank in Evolving Tree Graphs." In Stochastic Processes and Applications, 375–90. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02825-1_16.

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Manuel, Paul, Bharati Rajan, Indra Rajasingh, and Amutha Alaguvel. "Tree Spanners, Cayley Graphs, and Diametrically Uniform Graphs." In Graph-Theoretic Concepts in Computer Science, 334–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39890-5_29.

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Conference papers on the topic "Tree graphs"

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Mayhew, Gregory L. "Rooted tree graphs and de Bruijn graphs." In 2010 IEEE Aerospace Conference. IEEE, 2010. http://dx.doi.org/10.1109/aero.2010.5446922.

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Nagoya, Takayuki. "Variants of Graph Matching for Tree-like Graphs." In 2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity). IEEE, 2015. http://dx.doi.org/10.1109/smartcity.2015.168.

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Jiang, Qiang-rong, and Yuan Gao. "Spanning-Tree Kernels on Graphs." In 2010 International Conference on Measuring Technology and Mechatronics Automation (ICMTMA 2010). IEEE, 2010. http://dx.doi.org/10.1109/icmtma.2010.69.

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Hong, Seok-Hee, Quan Nguyen, Amyra Meidiana, Jiaxi Li, and Peter Eades. "BC Tree-Based Proxy Graphs for Visualization of Big Graphs." In 2018 IEEE Pacific Visualization Symposium (PacificVis). IEEE, 2018. http://dx.doi.org/10.1109/pacificvis.2018.00011.

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Akiba, Takuya, Yoichi Iwata, Yosuke Sameshima, Naoto Mizuno, and Yosuke Yano. "Cut Tree Construction from Massive Graphs." In 2016 IEEE 16th International Conference on Data Mining (ICDM). IEEE, 2016. http://dx.doi.org/10.1109/icdm.2016.0089.

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Da San Martino, Giovanni, Nicolò Navarin, and Alessandro Sperduti. "A Tree-Based Kernel for Graphs." In Proceedings of the 2012 SIAM International Conference on Data Mining. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2012. http://dx.doi.org/10.1137/1.9781611972825.84.

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AIZENMAN, MICHAEL, and SIMONE WARZEL. "DISORDER-INDUCED DELOCALIZATION ON TREE GRAPHS." In Proceedings of the QMath11 Conference. WORLD SCIENTIFIC, 2011. http://dx.doi.org/10.1142/9789814350365_0008.

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Ma, Cherng-Min, Shu-Yen Wan, and Jiann-Der Lee. "Skeletonization on 3D tree-embedded graphs." In Medical Imaging 2003, edited by Milan Sonka and J. Michael Fitzpatrick. SPIE, 2003. http://dx.doi.org/10.1117/12.480126.

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KARUNO, YOSHIYUKI, and HIROSHI NAGAMOCHI. "MINIMIZING CAPACITATED TREE COVERS OF GRAPHS." In Proceedings of the 3rd Asian Applied Computing Conference. PUBLISHED BY IMPERIAL COLLEGE PRESS AND DISTRIBUTED BY WORLD SCIENTIFIC PUBLISHING CO., 2007. http://dx.doi.org/10.1142/9781860948534_0012.

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Da Silva, Thiago Gouveia. "The Minimum Labeling Spanning Tree and Related Problems." In XXXII Concurso de Teses e Dissertações da SBC. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/ctd.2019.6333.

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The minimum labeling spanning tree problem (MLSTP) is a combinatorial optimization problem that consists in finding a spanning tree in a simple edge-labeled graph, i.e., a graph in which each edge has one label associated, by using a minimum number of labels. It is an NP-hard problem that has attracted substantial research attention in recent years. In its turn, the generalized minimum labeling spanning tree problem (GMLSTP) is a generalization of the MLSTP that allows the situation in which multiple labels can be assigned to an edge. Both problems have several practical applications in important areas such as computer network design, multimodal transportation network design, and data compression. The thesis addresses several connectivity problems defined over edge-labeled graphs, in special the minimum labeling spanning tree problem and its generalized version. The contributions in the work can be classified between theoretical and practical. On the theoretical side, it has introduced new useful concepts, definitions, properties and theorems regarding edge-labeled graphs, as well as a polyhedral study on the GMLSTP. On the practical side, we have proposed new heuristics and new mathematical formulations and branch-and-cut algorithms. The new approaches introduced have achieved the best results for both heuristic and exact methods in comparison with the state-of-the-art.
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Reports on the topic "Tree graphs"

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Mahoney, James. Tree Graphs and Orthogonal Spanning Tree Decompositions. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.2939.

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Flowerday, Kaelyn. Unfolding Trees and Symmetrically-Associated Graphs. Portland State University Library, November 2015. http://dx.doi.org/10.15760/honors.210.

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Sullivan, Blair D., Dinesh P. Weerapurage, and Christopher S. Groer. Parallel Algorithms for Graph Optimization using Tree Decompositions. Office of Scientific and Technical Information (OSTI), June 2012. http://dx.doi.org/10.2172/1042920.

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Blair, J. R. S., and B. W. Peyton. An introduction to chordal graphs and clique trees. Office of Scientific and Technical Information (OSTI), November 1992. http://dx.doi.org/10.2172/10145949.

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Blair, J. R. S., and B. W. Peyton. An introduction to chordal graphs and clique trees. Office of Scientific and Technical Information (OSTI), November 1992. http://dx.doi.org/10.2172/6560471.

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Sonderman, David L., Everette D. Rast, and Everette D. Rast. Changes in hardwood growing-stock tree grades. Broomall, PA: U.S. Department of Agriculture, Forest Service, Northeastern Forest Experimental Station, 1987. http://dx.doi.org/10.2737/ne-rp-608.

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Dror, Moshe, Bezalel Gavish, and Jean Choquette. Directed Steiner Tree Problem on a Graph: Models, Relaxations, and Algorithms. Fort Belvoir, VA: Defense Technical Information Center, August 1988. http://dx.doi.org/10.21236/ada199769.

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Pawagi, S., and I. V. Ramakrishnan. On Using Inverted Trees for Updating Graph Properties. Fort Belvoir, VA: Defense Technical Information Center, May 1985. http://dx.doi.org/10.21236/ada160135.

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Pawagi, Shaunak, and I. V. Ramakrishnan. On Using Multiple Inverted Trees for Parallel Updating of Graph Properties. Fort Belvoir, VA: Defense Technical Information Center, May 1985. http://dx.doi.org/10.21236/ada166058.

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Qi, Fei, Zhaohui Xia, Gaoyang Tang, Hang Yang, Yu Song, Guangrui Qian, Xiong An, Chunhuan Lin, and Guangming Shi. A Graph-based Evolutionary Algorithm for Automated Machine Learning. Web of Open Science, December 2020. http://dx.doi.org/10.37686/ser.v1i2.77.

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As an emerging field, Automated Machine Learning (AutoML) aims to reduce or eliminate manual operations that require expertise in machine learning. In this paper, a graph-based architecture is employed to represent flexible combinations of ML models, which provides a large searching space compared to tree-based and stacking-based architectures. Based on this, an evolutionary algorithm is proposed to search for the best architecture, where the mutation and heredity operators are the key for architecture evolution. With Bayesian hyper-parameter optimization, the proposed approach can automate the workflow of machine learning. On the PMLB dataset, the proposed approach shows the state-of-the-art performance compared with TPOT, Autostacker, and auto-sklearn. Some of the optimized models are with complex structures which are difficult to obtain in manual design.
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