Relevant bibliographies by topics / Vertex's Neighbors

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

Academic literature on the topic 'Vertex's Neighbors'

Author: Grafiati
Published: 5 June 2025
Last updated: 15 July 2025

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Journal articles on the topic "Vertex's Neighbors"

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Gou, Yutong, Jianyang Gao, Yuexuan Xu, and Cheng Long. "SymphonyQG: Towards Symphonious Integration of Quantization and Graph for Approximate Nearest Neighbor Search." Proceedings of the ACM on Management of Data 3, no. 1 (2025): 1–26. https://doi.org/10.1145/3709730.

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Approximate nearest neighbor (ANN) search in high-dimensional Euclidean space has a broad range of applications. Among existing ANN algorithms, graph-based methods have shown superior performance in terms of the time-accuracy trade-off. However, they face performance bottlenecks due to the random memory accesses caused by the searching process on the graph indices and the costs of computing exact distances to guide the searching process. To relieve the bottlenecks, a recent method named NGT-QG makes an attempt by integrating quantization and graph. It (1) replicates and stores the quantization
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Zhang, Chenghan, Yuanyuan Zhu, and Lijun Chang. "A Local Search Approach to Efficient ( k,p )-Core Maintenance." Proceedings of the ACM on Management of Data 3, no. 1 (2025): 1–26. https://doi.org/10.1145/3709654.

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The (( k,p ))-core model was recently proposed to capture engagement dynamics by considering both intra-community interactions (i.e., the k -core structure) and inter-community interactions (i.e., the p -fraction property). It is a refinement of the classic k -core, by introducing an extra parameter p to customize the engagement within a community at a finer granularity. In this paper, we study the problem of maintaining all (k,p)-cores (essentially, maintaining the p-numbers for all vertices) for dynamic graphs. The existing Global approach conducts a global peeling, almost from scratch, for
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Naqvi, Shabbar, Muhammad Salman, Muhammad Ehtisham, Muhammad Fazil, and Masood Ur Rehman. "On the neighbor-distinguishing in generalized Petersen graphs." AIMS Mathematics 6, no. 12 (2021): 13734–45. http://dx.doi.org/10.3934/math.2021797.

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<abstract><p>In a connected graph $ G $, two adjacent vertices are said to be neighbors of each other. A vertex $ v $ adjacently distinguishes a pair $ (x, y) $ of two neighbors in $ G $ if the number of edges in $ v $-$ x $ geodesic and the number of edges in $ v $-$ y $ geodesic differ by one. A set $ S $ of vertices of $ G $ is a neighbor-distinguishing set for $ G $ if every two neighbors in $ G $ are adjacently distinguished by some element of $ S $. In this paper, we consider two families of generalized Petersen graphs and distinguish every two neighbors in these graphs by in
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Wang, Yanling, and Shiying Wang. "The 3-Good-Neighbor Connectivity of Modified Bubble-Sort Graphs." Mathematical Problems in Engineering 2020 (October 28, 2020): 1–18. http://dx.doi.org/10.1155/2020/7845987.

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Let G = V G , E G be a connected graph. A subset F ⊆ V G is called a g -good-neighbor cut if G − F is disconnected and each vertex of G − F has at least g neighbors. The g -good-neighbor connectivity of G is the minimum cardinality of g -good-neighbor cuts. The n -dimensional modified bubble-sort graph MB n is a special Cayley graph. It has many good properties. In this paper, we prove that the 3-good-neighbor connectivity of MB n is 8 n − 24 for n ≥ 6 .
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Kim, Kijung. "The Italian Domination Numbers of Some Products of Directed Cycles." Mathematics 8, no. 9 (2020): 1472. http://dx.doi.org/10.3390/math8091472.

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An Italian dominating function on a digraph D with vertex set V(D) is defined as a function f:V(D)→{0,1,2} such that every vertex v∈V(D) with f(v)=0 has at least two in-neighbors assigned 1 under f or one in-neighbor w with f(w)=2. In this article, we determine the exact values of the Italian domination numbers of some products of directed cycles.
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GU, MEI-MEI, RONG-XIA HAO, and AI-MEI YU. "The 1-Good-Neighbor Conditional Diagnosability of Some Regular Graphs." Journal of Interconnection Networks 17, no. 03n04 (2017): 1741001. http://dx.doi.org/10.1142/s0219265917410018.

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The g-good-neighbor conditional diagnosability is the maximum number of faulty vertices a network can guarantee to identify, under the condition that every fault-free vertex has at least g fault-free neighbors. In this paper, we study the 1-good-neighbor conditional diagnosabilities of some general k-regular k-connected graphs G under the PMC model and the MM* model. The main result [Formula: see text] under some conditions is obtained, where l is the maximum number of common neighbors between any two adjacent vertices in G. Moreover, the following results are derived: [Formula: see text] for
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Sheikholeslami, Seyed Mahmoud, Asghar Bodaghli, and Lutz Volkmann. "Twin signed Roman domination numbers in directed graphs." Tamkang Journal of Mathematics 47, no. 3 (2016): 357–71. http://dx.doi.org/10.5556/j.tkjm.47.2016.2035.

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Let $D$ be a finite simple digraph with vertex set $V(D)$ and arc set $A(D)$. A twin signed Roman dominating function (TSRDF) on the digraph $D$ is a function $f:V(D)\rightarrow\{-1,1,2\}$ satisfying the conditions that (i) $\sum_{x\in N^-[v]}f(x)\ge 1$ and $\sum_{x\in N^+[v]}f(x)\ge 1$ for each $v\in V(D)$, where $N^-[v]$ (resp. $N^+[v]$) consists of $v$ and all in-neighbors (resp. out-neighbors) of $v$, and (ii) every vertex $u$ for which $f(u)=-1$ has an in-neighbor $v$ and an out-neighbor $w$ for which $f(v)=f(w)=2$. The weight of an TSRDF $f$ is $\omega(f)=\sum_{v\in V(D)}f(v)$. The twin
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Amjadi, J., and M. Soroudi. "Twin signed total Roman domination numbers in digraphs." Asian-European Journal of Mathematics 11, no. 03 (2018): 1850034. http://dx.doi.org/10.1142/s1793557118500341.

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Let [Formula: see text] be a finite simple digraph with vertex set [Formula: see text] and arc set [Formula: see text]. A twin signed total Roman dominating function (TSTRDF) on the digraph [Formula: see text] is a function [Formula: see text] satisfying the conditions that (i) [Formula: see text] and [Formula: see text] for each [Formula: see text], where [Formula: see text] (respectively [Formula: see text]) consists of all in-neighbors (respectively out-neighbors) of [Formula: see text], and (ii) every vertex [Formula: see text] for which [Formula: see text] has an in-neighbor [Formula: see
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Amjadi, Jafar, and Fatemeh Pourhosseini. "Signed double Roman domination numbers in digraphs." Annals of the University of Craiova - Mathematics and Computer Science Series 48, no. 1 (2021): 194–205. http://dx.doi.org/10.52846/ami.v48i1.1305.

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"Let $D=(V,A)$ be a finite simple digraph. A signed double Roman dominating function (SDRD-function) on the digraph $D$ is a function $f:V(D)\rightarrow\{-1,1,2, 3\}$ satisfying the following conditions: (i) $\sum_{x\in N^-[v]}f(x)\ge 1$ for each $v\in V(D)$, where $N^-[v]$ consist of $v$ and all in-neighbors of $v$, and (ii) if $f(v)=-1$, then the vertex $v$ must have at least two in-neighbors assigned 2 under $f$ or one in-neighbor assigned 3, while if $f(v)=1$, then the vertex $v$ must have at least one in-neighbor assigned 2 or 3. The weight of a SDRD-function $f$ is the value $\sum_{x\in
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Goebbels, Steffen, Frank Gurski, and Dominique Komander. "The knapsack problem with special neighbor constraints." Mathematical Methods of Operations Research 95, no. 1 (2021): 1–34. http://dx.doi.org/10.1007/s00186-021-00767-5.

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AbstractThe knapsack problem is one of the simplest and most fundamental NP-hard problems in combinatorial optimization. We consider two knapsack problems which contain additional constraints in the form of directed graphs whose vertex set corresponds to the item set. In the one-neighbor knapsack problem, an item can be chosen only if at least one of its neighbors is chosen. In the all-neighbors knapsack problem, an item can be chosen only if all its neighbors are chosen. For both problems, we consider uniform and general profits and weights. We prove upper bounds for the time complexity of th
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Dissertations / Theses on the topic "Vertex's Neighbors"

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Bergougnoux, Benjamin. "Matrix decompositions and algorithmic applications to (hyper)graphs." Thesis, Université Clermont Auvergne‎ (2017-2020), 2019. http://www.theses.fr/2019CLFAC025/document.

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Durant ces dernières décennies, d'importants efforts et beaucoup de café ont été dépensés en vue de caractériser les instances faciles des problèmes NP-difficiles. Dans ce domaine de recherche, une approche s'avère être redoutablement efficace : la théorie de la complexité paramétrée introduite par Downey et Fellows dans les années 90.Dans cette théorie, la complexité d'un problème n'est plus mesurée uniquement en fonction de la taille de l'instance, mais aussi en fonction d'un paramètre .Dans cette boite à outils, la largeur arborescente est sans nul doute un des paramètres de graphe les plus
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Matula, Radek. "Grafická reprezentace grafů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2009. http://www.nusl.cz/ntk/nusl-236753.

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This Master Thesis deals with the drawing algorithms of graphs known from the mathematical theory. These algorithms deals with an appropriate distribution of the graph vertices in order to obtain the most clear and readable graphs for human readers. The main objective of this work was also to implement the drawing algorithm in the application that would allow to edit the graph. This work deals also with graphs representation in computers.
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Books on the topic "Vertex's Neighbors"

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Zhang, Ping. Color-Induced Graph Colorings: Vertex and Neighbor Distinguishing Edge Colorings of Graphs. Springer International Publishing AG, 2015.

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Book chapters on the topic "Vertex's Neighbors"

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Guo, Jiangyan, and Elkin Vumar. "The Vertex-Neighbor-Integrity of Digraphs." In Computational Science – ICCS 2007. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72588-6_60.

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Li, Yueping. "A New Vertex Similarity Metric for Community Discovery: A Distance Neighbor Model." In Intelligent Information and Database Systems. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20039-7_23.

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Vicol Paul, Delgrande James, and Schaub Torsten. "A Minimization-Based Approach to Iterated Multi-Agent Belief Change." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2016. https://doi.org/10.3233/978-1-61499-672-9-1221.

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We investigate minimization-based approaches to iterated belief change in multi-agent systems. A network of agents is represented by an undirected graph, where propositional formulas are associated with vertices. Information is shared between vertices via a procedure where each vertex minimizes disagreement with other vertices in the graph. Each iterative approach takes into account the proximity between vertices, with the underlying assumption that information from nearby sources is given higher priority than information from more distant sources. We have identified two main approaches to iteration: in the first approach, a vertex takes into account the information at its immediate neighbours only, and information from more distant vertices is propagated via iteration; in the second approach, a vertex first takes into account information from distance-1 neighbours, then from distance-2 neighbours, and so on, in a prioritized fashion. There prove to be three distinct ways to define the second approach, so in total we have four types of iteration. We define these types formally, find relationships between them, and investigate their basic logical properties. We also implemented the approaches in a software system called Equibel.
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Dorogovtsev, Sergey N., and José F. F. Mendes. "Epidemics and Spreading Phenomena." In The Nature of Complex Networks. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780199695119.003.0007.

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Abstract In this chapter we mainly focus on the results of activation processes in networks and on various combinations of activation and deactivation processes. The bootstrap percolation problem is about the basic activation process on networks, in which vertices can be in active and inactive states. A vertex becomes active when the number of its active neighbours exceeds some threshold; and once active, a vertex never becomes inactive (Adler and Aharony, 1988; Adler, 1991). This is one of the spreading processes with discontinuous phase transitions (Bizhani, Paczuski, and Grassberger, 2012). Let us define bootstrap percolation on undirected graphs in more strict terms. In the initial state, a fraction f of vertices is active (seed vertices). These vertices are chosen uniformly at random. Each inactive vertex becomes active if it has at least kb active nearest neighbours. Here we introduce the subscript ‘b’ to distinguish this threshold from a threshold in the k-core percolation problem.
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Dorogovtsev, Sergey N., and José F. F. Mendes. "Walks and Search." In The Nature of Complex Networks. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780199695119.003.0010.

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Abstract Milgram’s algorithm is actually the standard one in computer science, belonging to the class of decentralized search algorithms. A number of routing algorithms exploit geographic information about vertices of communication networks (Karp and Kung, 2000). The simplest geographic routing implements the greedy routing algorithm assuming that: (i) each vertex in a network has its geographic coordinate, and (ii) a vertex forwards messages (packets) to that its nearest neighbour in the network, which is geographically closest to the destination.
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Li, Guanfeng, and Zongmin Ma. "A Fuzzy RDF Graph-Matching Method Based on Neighborhood Similarity." In Advances in Data Mining and Database Management. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8446-9.ch009.

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With the popularity of fuzzy RDF data, identifying correspondences among these data sources is an important task. Although there are some solutions addressing this problem in classical RDF datasets, existing methods do not consider fuzzy information which is an important property existing in fuzzy RDF graphs. In this article, we apply fuzzy graph to model the fuzzy RDF datasets and propose a novel similarity-oriented RDF graph matching approach, which makes full use of the 1-hop neighbor vertex and edge label information, and takes into account the fuzzy information of a fuzzy RDF graph. Based on the neighborhood similarity, we propose a breadth-first branch-and-bound method for fuzzy RDF graph matching, which uses a state space search method and uses truncation parameters to constrain the search. This algorithm can be used to identify the matched pairs.
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Marwaha, Hitesh, Anurag Sharma, and Vikrant Sharma. "Role of Graph Theory in Computational Neuroscience." In Futuristic Design and Intelligent Computational Techniques in Neuroscience and Neuroengineering. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-7433-1.ch005.

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Neuroscience is the study of the brain and its impact on behavior and cognitive functions. Computational neuroscience is the subfield that deals with the study of the ability of the brain to think and compute. It also analyzes various electrical and chemical signals that take place in the brain to represent and process the information. In this chapter, a special focus will be given on the processing of signals by the brain to solve the problems. In the second section of the chapter, the role of graph theory is discussed to analyze the pattern of neurons. Graph-based analysis reveals meaningful information about the topological architecture of human brain networks. The graph-based analysis also discloses the networks in which most nodes are not neighbors of each other but can be reached from every other node by a small number of steps. In the end, it is concluded that by using the various operations of graph theory, the vertex centrality, betweenness, etc. can be computed to identify the dominant neurons for solving different types of computational problems.
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Conference papers on the topic "Vertex's Neighbors"

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Gao, Zhongpai, Junchi Yan, Guangtao Zhai, and Xiaokang Yang. "Learning Spectral Dictionary for Local Representation of Mesh." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/95.

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For meshes, sharing the topology of a template is a common and practical setting in face-, hand-, and body-related applications. Meshes are irregular since each vertex's neighbors are unordered and their orientations are inconsistent with other vertices. Previous methods use isotropic filters or predefined local coordinate systems or learning weighting matrices for each vertex of the template to overcome the irregularity. Learning weighting matrices for each vertex to soft-permute the vertex's neighbors into an implicit canonical order is an effective way to capture the local structure of each
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Xu, Yanan, Yanmin Zhu, Yanyan Shen, and Jiadi Yu. "Learning Shared Vertex Representation in Heterogeneous Graphs with Convolutional Networks for Recommendation." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/642.

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Collaborative Filtering (CF) is among the most successful techniques in recommendation tasks. Recent works have shown a boost of performance of CF when introducing the pairwise relationships between users and items or among items (users) using interaction data. However, these works usually only utilize one kind of information, i.e., user preference in a user-item interaction matrix or item dependency in interaction sequences which can limit the recommendation performance. In this paper, we propose to mine three kinds of information (user preference, item dependency, and user similarity on beha
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Domingues, Kenny, and Ana Silva. "On the Partial Grundy Number of a Graph Minus a Matching." In Encontro de Teoria da Computação. Sociedade Brasileira de Computação - SBC, 2022. http://dx.doi.org/10.5753/etc.2022.223134.

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Given a k-coloring S1, . . . , Sk of G, a vertex in Si is said to be greedy if it has neighbors in Sj, for every j < i. Thus, a Grundy coloring can be seen as a coloring where every vertex is greedy. In contrast, a partial Grundy coloring is defined as a coloring in which each color class has at least one greedy vertex; the maximum number of colors in a partial Grundy coloring is denoted by ∂Γ(G). In this paper, we investigate some conjectures about Grundy colorings, already known not to hold, adapted to partial Grundy colorings. We prove that, while two of them also do not hold, a third do
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Zhou, Zhongxin, Fan Zhang, Xuemin Lin, Wenjie Zhang, and Chen Chen. "K-Core Maximization: An Edge Addition Approach." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/676.

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A popular model to measure the stability of a network is k-core - the maximal induced subgraph in which every vertex has at least k neighbors. Many studies maximize the number of vertices in k-core to improve the stability of a network. In this paper, we study the edge k-core problem: Given a graph G, an integer k and a budget b, add b edges to non-adjacent vertex pairs in G such that the k-core is maximized. We prove the problem is NP-hard and APX-hard. A heuristic algorithm is proposed on general graphs with effective optimization techniques. Comprehensive experiments on 9 real-life datasets
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Weffort-Santos, Celso A., Christiane N. Campos, and Rafael C. S. Schouery. "Proper gap-labellings: on the edge and vertex variants." In XXXII Concurso de Teses e Dissertações da SBC. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/ctd.2019.6343.

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Given a simple graph G, an ordered pair (π, cπ) is said to be a gap- [k]-edge-labelling (resp. gap-[k]-vertex-labelling) ofG ifπ is an edge-labelling (vertex-labelling) on the set {1, . . . , k}, and cπ is a proper vertex-colouring such that every vertex of degree at least two has its colour induced by the largest difference among the labels of its incident edges (neighbours). The decision problems associated with these labellings are NP-complete for k ≥ 3, and even when k = 2 for some classes of graphs. This thesis presents a study of the computational complexity of these problems, structural
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Lima, João P., Anne C. Rocha, Alexandre Arruda, and Dmontier Jr. "Application of Weighted Partial Max-SAT for Post-improvement of the Multiple Traveling Salesman Problem." In Workshop Brasileiro de Lógica. Sociedade Brasileira de Computação, 2024. http://dx.doi.org/10.5753/wbl.2024.2458.

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Advances allow SAT solvers to be used to solve problems in the industrial sector. Therefore, in this paper, we reduce the multiple traveling salesman problem to a weighted partial max-SAT, with the aim of increasing the quality of the solution at a reduced computational cost. A version of Clarke and Wright’s saving algorithm has been implemented to create the initial solution, while the 2-opt algorithm is applied to each route to improve the routes, the search space is extended by adding k nearest neighbors of each vertex so that post-improvement can be performed by the SAT solver. Benchmarks
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Thomas, Tina Maria, Jiss Varghese, and Shiney Thomas. "An improvement to vertex decimation: Finding referencing neighbors for low distortion in 3D steganography." In 2013 International Conference on Control Communication and Computing (ICCC). IEEE, 2013. http://dx.doi.org/10.1109/iccc.2013.6731661.

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Viana, Luiz Alberto, and Manoel Campêlo. "The Least-Dependency Constrained Spanning Tree Problem." In Encontro de Teoria da Computação. Sociedade Brasileira de Computação - SBC, 2017. http://dx.doi.org/10.5753/etc.2017.3190.

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We introduce the Least-Dependency Constrained Spanning Tree Problem, which consists of finding a spanning tree where each edge has at least one edge of its dependency set, if non-empty, also in the tree. The dependencies on the input graph G are described by a digraph D where the vertices are the edges of G, and the in-neighbors of a vertex are its dependency set. We show that the optimization problem is NP-hard even if G is a chordal cactus with maximum degree 3 or diameter at most 2, and D is a disjoint union of arborescences of height 2. The same complexity is proved when G is planar bipart
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Du, Lun, Zhicong Lu, Yun Wang, Guojie Song, Yiming Wang, and Wei Chen. "Galaxy Network Embedding: A Hierarchical Community Structure Preserving Approach." 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.2018/287.

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Network embedding is a method of learning a low-dimensional vector representation of network vertices under the condition of preserving different types of network properties. Previous studies mainly focus on preserving structural information of vertices at a particular scale, like neighbor information or community information, but cannot preserve the hierarchical community structure, which would enable the network to be easily analyzed at various scales. Inspired by the hierarchical structure of galaxies, we propose the Galaxy Network Embedding (GNE) model, which formulates an optimization pro
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Andrade, Matheus Guedes de, Franklin De Lima Marquezino, and Daniel Ratton Figueiredo. "Characterizing the Relationship Between Unitary Quantum Walks and Non-Homogeneous Random Walks." In Concurso de Teses e Dissertações da SBC. Sociedade Brasileira de Computação, 2021. http://dx.doi.org/10.5753/ctd.2021.15756.

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Quantum walks on graphs are ubiquitous in quantum computing finding a myriad of applications. Likewise, random walks on graphs are a fundamental building block for a large number of algorithms with diverse applications. While the relationship between quantum and random walks has been recently discussed in specific scenarios, this work establishes a formal equivalence between the two processes on arbitrary finite graphs and general conditions for shift and coin operators. It requires empowering random walks with time heterogeneity, where the transition probability of the walker is non-uniform a
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