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Relevant bibliographies by topics / Graph classification / Dissertations / Theses

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Dissertations / Theses on the topic 'Graph classification'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 April 2022

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1

Wainer, L. J. "Online graph-based learning for classification." Thesis, University College London (University of London), 2008. http://discovery.ucl.ac.uk/1446151/.

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The aim of this thesis is to develop online kernel based algorithms for learning clas sification functions over a graph. An important question in machine learning is: how to learn functions in a high dimension One of the benefits of using a graphical representation of data is that it can provide a dimensionality reduction of the data to the number of nodes plus edges in the graph. Graphs are useful discrete repre sentations of data that have already been used successfully to incorporate structural information in data to aid in semi-supervised learning techniques. In this thesis, an online lear

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Saldanha, Richard A. "Graph-theoretic methods in discrimination and classification." Thesis, University of Oxford, 1998. https://ora.ox.ac.uk/objects/uuid:3a06dee1-00e9-4b56-be8e-e991a570ced6.

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This thesis is concerned with the graphical modelling of multivariate data. The main aim of graphical modelling is to provide an easy to understand visual representation of, often complex, data relationships by fitting graphs to data. The graphs consist of nodes denoting random variables and connecting lines or edges are used to depict variable dependencies. Equivalently, the absence of particular edges in a graph describe conditional independencies between random variables. The resulting structure is called a conditional independence graph. The use of conditional independence graphs as a guid

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Ketkar, Nikhil S. "Empirical comparison of graph classification and regression algorithms." Pullman, Wash. : Washington State University, 2009. http://www.dissertations.wsu.edu/Dissertations/Spring2009/n_ketkar_042409.pdf.

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Thesis (Ph. D.)--Washington State University, May 2009.<br>Title from PDF title page (viewed on June 3, 2009). "School of Electrical Engineering and Computer Science." Includes bibliographical references (p. 101-108).

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Ferrer, Sumsi Miquel. "Theory and Algorithms on the Median Graph. Application to Graph-based Classification and Clustering." Doctoral thesis, Universitat Autònoma de Barcelona, 2008. http://hdl.handle.net/10803/5788.

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Donat un conjunt d'objectes, el concepte genèric de mediana està deﬁnit com l'objecte amb la suma de distàncies a tot el conjunt, més petita. Sovint, aquest concepte és usat per a obtenir el representant del conjunt. <br/>En el reconeixement estructural de patrons, els grafs han estat usats normalment per a representar objectes complexos. En el domini dels grafs, el concepte de mediana és conegut com median graph. Potencialment, té les mateixes aplicacions que el concepte de mediana per poder ser usat com a representant d'un conjunt de grafs. <br/>Tot i la seva simple deﬁnició i

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Childs, Liam, Zoran Nikoloski, Patrick May, and Dirk Walther. "Identification and classification of ncRNA molecules using graph properties." Universität Potsdam, 2009. http://opus.kobv.de/ubp/volltexte/2010/4519/.

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The study of non-coding RNA genes has received increased attention in recent years fuelled by accumulating evidence that larger portions of genomes than previously acknowledged are transcribed into RNA molecules of mostly unknown function, as well as the discovery of novel non-coding RNA types and functional RNA elements. Here, we demonstrate that specific properties of graphs that represent the predicted RNA secondary structure reflect functional information. We introduce a computational algorithm and an associated web-based tool (GraPPLE) for classifying non-coding RNA molecules as functiona

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Ersahin, Kaan. "Segmentation and classification of polarimetric SAR data using spectral graph partitioning." Thesis, University of British Columbia, 2009. http://hdl.handle.net/2429/14607.

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Polarimetric Synthetic Aperture Radar (POLSAR) data have been commercially available for the last few years, which has increased demand for its operational use in remote sensing applications. Segmentation and classification of image data are important tasks for POLSAR data analysis and interpretation, which often requires human interaction. Existing strategies for automated POLSAR data analysis have utilized the polarimetric attributes of pixels, which involve target decompositions based on physical, mathematical or statistical models. A well-established and widely-used technique is the Wisha

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Lee, Zed Heeje. "A graph representation of event intervals for efficient clustering and classification." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-281947.

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Sequences of event intervals occur in several application domains, while their inherent complexity hinders scalable solutions to tasks such as clustering and classification. In this thesis, we propose a novel spectral embedding representation of event interval sequences that relies on bipartite graphs. More concretely, each event interval sequence is represented by a bipartite graph by following three main steps: (1) creating a hash table that can quickly convert a collection of event interval sequences into a bipartite graph representation, (2) creating and regularizing a bi-adjacency matrix

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Wu, Jindong. "Pooling strategies for graph convolution neural networks and their effect on classification." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-288953.

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With the development of graph neural networks, this novel neural network has been applied in a broader and broader range of fields. One of the thorny problems researchers face in this field is selecting suitable pooling methods for a specific research task from various existing pooling methods. In this work, based on the existing mainstream graph pooling methods, we develop a benchmark neural network framework that can be used to compare these different graph pooling methods. By using the framework, we compare four mainstream graph pooling methods and explore their characteristics. Furthermore

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Chandra, Nagasai. "Node Classification on Relational Graphs using Deep-RGCNs." DigitalCommons@CalPoly, 2021. https://digitalcommons.calpoly.edu/theses/2265.

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Knowledge Graphs are fascinating concepts in machine learning as they can hold usefully structured information in the form of entities and their relations. Despite the valuable applications of such graphs, most knowledge bases remain incomplete. This missing information harms downstream applications such as information retrieval and opens a window for research in statistical relational learning tasks such as node classification and link prediction. This work proposes a deep learning framework based on existing relational convolutional (R-GCN) layers to learn on highly multi-relational data cha

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Lamont, Morné Michael Connell. "Binary classification trees : a comparison with popular classification methods in statistics using different software." Thesis, Stellenbosch : Stellenbosch University, 2002. http://hdl.handle.net/10019.1/52718.

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Thesis (MComm) -- Stellenbosch University, 2002.<br>ENGLISH ABSTRACT: Consider a data set with a categorical response variable and a set of explanatory variables. The response variable can have two or more categories and the explanatory variables can be numerical or categorical. This is a typical setup for a classification analysis, where we want to model the response based on the explanatory variables. Traditional statistical methods have been developed under certain assumptions such as: the explanatory variables are numeric only and! or the data follow a multivariate normal distributio

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Altun, Gulsah. "Machine Learning and Graph Theory Approaches for Classification and Prediction of Protein Structure." Digital Archive @ GSU, 2008. http://digitalarchive.gsu.edu/cs_diss/31.

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Recently, many methods have been proposed for the classification and prediction problems in bioinformatics. One of these problems is the protein structure prediction. Machine learning approaches and new algorithms have been proposed to solve this problem. Among the machine learning approaches, Support Vector Machines (SVM) have attracted a lot of attention due to their high prediction accuracy. Since protein data consists of sequence and structural information, another most widely used approach for modeling this structured data is to use graphs. In computer science, graph theory has been widel

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Jackson, Eugenie Marie. "Explorations in the classification of vertices as good or bad." [Johnson City, Tenn. : East Tennessee State University], 2001. http://etd-submit.etsu.edu/etd/theses/available/etd-0310101-153932/unrestricted/jacksone.pdf.

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Seeland, Madeleine [Verfasser], Burkhard [Akademischer Betreuer] Rost, and Stefan [Akademischer Betreuer] Kramer. "Structural Graph Clustering: Scalable Methods and Applications for Graph Classification and Regression / Madeleine Seeland. Gutachter: Burkhard Rost ; Stefan Kramer. Betreuer: Burkhard Rost." München : Universitätsbibliothek der TU München, 2014. http://d-nb.info/1058434500/34.

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Rinke, Sebastian. "Analysis and Adaption of Graph Mapping Algorithms for Regular Graph Topologies." Master's thesis, Universitätsbibliothek Chemnitz, 2009. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-200901453.

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The Message Passing Interface (MPI) standard defines virtual topologies that can be applied to systems of cooperating processes. Among issues regarding a more convenient namespace this may be used to optimize the placement of MPI processes in order to reduce communication time. That means, the processes with their main communication paths represent a graph that has to be cost efficiently mapped onto the graph representing the actual communication network. In this context, this work analyses and compares state-of-the-art task mapping strategies with respect to running time and their quality of

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Pavuluri, Manoj Kumar. "Fuzzy decision tree classification for high-resolution satellite imagery /." free to MU campus, to others for purchase, 2003. http://wwwlib.umi.com/cr/mo/fullcit?p1418056.

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Marcusanu, Mihaela C. "The classification of l₁-embeddable fullerenes." Bowling Green State University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1180115123.

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Schenker, Adam. "Graph-Theoretic Techniques for Web Content Mining." [Tampa, Fla.] : University of South Florida, 2003. http://purl.fcla.edu/fcla/etd/SFE0000143.

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Elsner, Ulrich. "Graph partitioning - a survey." Universitätsbibliothek Chemnitz, 2005. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200501047.

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Many problems appearing in scientific computing and other areas can be formulated as a graph partitioning problems. Examples include data distribution for parallel computers, decomposition of sparse matrices and VLSI-design. In this survey we present the graph partitioning problem, describe some applications and introduce many of the algorithms used to solve the problem.

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Neggaz, Mohammed Yessin. "Automatic classification of dynamic graphs." Thesis, Bordeaux, 2016. http://www.theses.fr/2016BORD0169/document.

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Les réseaux dynamiques sont constitués d’entités établissant des contacts les unes avec les autres dans le temps. Un défi majeur dans les réseaux dynamiques est de prédire les modèles de mobilité et de décider si l’évolution de la topologie satisfait aux exigences du succès d’un algorithme donné. Les types de dynamique résultant de ces réseaux sont variés en échelle et en nature. Par exemple,certains de ces réseaux restent connexes tout le temps; d’autres sont toujours déconnectés mais offrent toujours une sorte de connexité dans le temps et dans l’espace(connexité temporelle); d’autres sont c

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Trinks, Martin. "Graph polynomials and their representations." Doctoral thesis, Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola", 2012. http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-94991.

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Graph polynomials are polynomials associated to graphs that encode the number of subgraphs with given properties. We list different frameworks used to define graph polynomials in the literature. We present the edge elimination polynomial and introduce several graph polynomials equivalent to it. Thereby, we connect a recursive definition to the counting of colorings and to the counting of (spanning) subgraphs. Furthermore, we define a graph polynomial that not only generalizes the mentioned, but also many of the well-known graph polynomials, including the Potts model, the matching polynomial, t

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Karunaratne, Thashmee M. "Learning predictive models from graph data using pattern mining." Doctoral thesis, Stockholms universitet, Institutionen för data- och systemvetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-100713.

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Learning from graphs has become a popular research area due to the ubiquity of graph data representing web pages, molecules, social networks, protein interaction networks etc. However, standard graph learning approaches are often challenged by the computational cost involved in the learning process, due to the richness of the representation. Attempts made to improve their efficiency are often associated with the risk of degrading the performance of the predictive models, creating tradeoffs between the efficiency and effectiveness of the learning. Such a situation is analogous to an optimizatio

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Vasilyeva, Elena, Maik Thiele, Christof Bornhövd, and Wolfgang Lehner. "Considering User Intention in Differential Graph Queries." IGI Global, 2015. https://tud.qucosa.de/id/qucosa%3A72931.

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Empty answers are a major problem by processing pattern matching queries in graph databases. Especially, there can be multiple reasons why a query failed. To support users in such situations, differential queries can be used that deliver missing parts of a graph query. Multiple heuristics are proposed for differential queries, which reduce the search space. Although they are successful in increasing the performance, they can discard query subgraphs relevant to a user. To address this issue, the authors extend the concept of differential queries and introduce top-k differential queries that cal

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Demco, Anthony A. "Graph kernel extensions and experiments with application to molecule classification, lead hopping and multiple targets." Thesis, University of Southampton, 2009. https://eprints.soton.ac.uk/66209/.

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The discovery of drugs that can effectively treat disease and alleviate pain is one of the core challenges facing modern medicine. The tools and techniques of machine learning have perhaps the greatest potential to provide a fast and effcient route toward the fabrication of novel and effective drugs. In particular, modern structured kernel methods have been successfully applied to range of problem domains and have been recently adapted for graph structures making them directly applicable to pharmaceutical drug discovery. Specifically graph structures have a natural fit with molecular data, in

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Hernández, Pérez Bernard. "Multi-View Object Recognition and Classification. Graph-BasedRepresentation of Visual Features and Structured Learning andPrediction." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-142486.

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Computer Vision is a subfield within artificial intelligence that includes methods for acquisition, processing, analysis and understanding of images to get results in numerical or symbolic form. The information provided by the results is used to make decisions.We do not speak ofComputer Vision in isolation, interaction with other fields is inevitable and deserve particular attention image processing, pattern recognition and Machine Learning. The main objective of this project is to analyze the behavior of visual feature extraction algorithms and their effectiveness in decision making. The dete

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Biyikoglu, Türker, Josef Leydold, and Peter F. Stadler. "Nodal Domain Theorems and Bipartite Subgraphs." Department of Statistics and Mathematics, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business, 2005. http://epub.wu.ac.at/626/1/document.pdf.

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The Discrete Nodal Domain Theorem states that an eigenfunction of the k-th largest eigenvalue of a generalized graph Laplacian has at most k (weak) nodal domains. We show that the number of strong nodal domains cannot exceed the size of a maximal induced bipartite subgraph and that this bound is sharp for generalized graph Laplacians. Similarly, the number of weak nodal domains is bounded by the size of a maximal bipartite minor. (author's abstract)<br>Series: Preprint Series / Department of Applied Statistics and Data Processing

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Wappler, Markus. "On Graph Embeddings and a new Minor Monotone Graph Parameter associated with the Algebraic Connectivity of a Graph." Doctoral thesis, Universitätsbibliothek Chemnitz, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-115518.

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We consider the problem of maximizing the second smallest eigenvalue of the weighted Laplacian of a (simple) graph over all nonnegative edge weightings with bounded total weight. We generalize this problem by introducing node significances and edge lengths. We give a formulation of this generalized problem as a semidefinite program. The dual program can be equivalently written as embedding problem. This is fifinding an embedding of the n nodes of the graph in n-space so that their barycenter is at the origin, the distance between adjacent nodes is bounded by the respective edge length, and the

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Reiß, Susanna. "Optimizing Extremal Eigenvalues of Weighted Graph Laplacians and Associated Graph Realizations." Doctoral thesis, Universitätsbibliothek Chemnitz, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-93599.

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This thesis deals with optimizing extremal eigenvalues of weighted graph Laplacian matrices. In general, the Laplacian matrix of a (weighted) graph is of particular importance in spectral graph theory and combinatorial optimization (e.g., graph partition like max-cut and graph bipartition). Especially the pioneering work of M. Fiedler investigates extremal eigenvalues of weighted graph Laplacians and provides close connections to the node- and edge-connectivity of a graph. Motivated by Fiedler, Göring et al. were interested in further connections between structural properties of the graph and

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Bocancea, Andreea. "Supervised Classification Leveraging Refined Unlabeled Data." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-119320.

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This thesis focuses on how unlabeled data can improve supervised learning classi-fiers in all contexts, for both scarce to abundant label situations. This is meant toaddress the limitations within supervised learning with regards to label availability.Extending the training set with unlabeled data can overcome issues such as selec-tion bias, noise and insufficient data. Based on the overall data distribution andthe initial set of labels, semi-supervised methods provide labels for additional datapoints. The semi-supervised approaches considered in this thesis belong to one ofthe following categ

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Kerracher, Natalie. "Tasks and visual techniques for the exploration of temporal graph data." Thesis, Edinburgh Napier University, 2017. http://researchrepository.napier.ac.uk/Output/977758.

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This thesis considers the tasks involved in exploratory analysis of temporal graph data, and the visual techniques which are able to support these tasks. There has been an enormous increase in the amount and availability of graph (network) data, and in particular, graph data that is changing over time. Understanding the mechanisms involved in temporal change in a graph is of interest to a wide range of disciplines. While the application domain may differ, many of the underlying questions regarding the properties of the graph and mechanism of change are the same. The research area of temporal g

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Cichocki, Radoslaw. "Classification of objects in images based on various object representations." Thesis, Blekinge Tekniska Högskola, Avdelningen för programvarusystem, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5774.

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Object recognition is a hugely researched domain that employs methods derived from mathematics, physics and biology. This thesis combines the approaches for object classification that base on two features – color and shape. Color is represented by color histograms and shape by skeletal graphs. Four hybrids are proposed which combine those approaches in different manners and the hybrids are then tested to find out which of them gives best results.<br>Mail the author at radoslaw.cichocki(at)gmail.com

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Mathieu, Bérangère. "Segmentation interactive multiclasse d'images par classification de superpixels et optimisation dans un graphe de facteurs." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30290/document.

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La segmentation est l'un des principaux thèmes du domaine de l'analyse d'images. Segmenter une image consiste à trouver une partition constituée de régions, c'est-à-dire d'ensembles de pixels connexes homogènes selon un critère choisi. L'objectif de la segmentation consiste à obtenir des régions correspondant aux objets ou aux parties des objets qui sont présents dans l'image et dont la nature dépend de l'application visée. Même s'il peut être très fastidieux, un tel découpage de l'image peut être facilement obtenu par un être humain. Il n'en est pas de même quand il s'agit de créer un program

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Srinivaasan, Gayathri. "Malicious Entity Categorization using Graph modelling." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-202980.

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Today, malware authors not only write malicious software but also employ obfuscation, polymorphism, packing and endless such evasive techniques to escape detection by Anti-Virus Products (AVP). Besides the individual behavior of malware, the relations that exist among them play an important role for improving malware detection. This work aims to enable malware analysts at F-Secure Labs to explore various such relationships between malicious URLs and file samples in addition to their individual behavior and activity. The current detection methods at F-Secure Labs analyze unknown URLs and file s

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Mantrach, Amin. "Novel measures on directed graphs and applications to large-scale within-network classification." Doctoral thesis, Universite Libre de Bruxelles, 2010. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210033.

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Ces dernières années, les réseaux sont devenus une source importante d’informations dans différents domaines aussi variés que les sciences sociales, la physique ou les mathématiques. De plus, la taille de ces réseaux n’a cessé de grandir de manière conséquente. Ce constat a vu émerger de nouveaux défis, comme le besoin de mesures précises et intuitives pour caractériser et analyser ces réseaux de grandes tailles en un temps raisonnable.<p>La première partie de cette thèse introduit une nouvelle mesure de similarité entre deux noeuds d’un réseau dirigé et pondéré :la covariance “sum-over-paths”

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Günther, Manuel [Verfasser]. "Statistical Gabor Graph Based Techniques for the Detection, Recognition, Classification, and Visualization of Human Faces / Manuel Günther." Aachen : Shaker, 2012. http://d-nb.info/1069046140/34.

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Gullstrand, Mattias, and Stefan Maraš. "Using Graph Neural Networks for Track Classification and Time Determination of Primary Vertices in the ATLAS Experiment." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-288505.

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Starting in 2027, the high-luminosity Large Hadron Collider (HL-LHC) will begin operation and allow higher-precision measurements and searches for new physics processes between elementary particles. One central problem that arises in the ATLAS detector when reconstructing event information is to separate the rare and interesting hard scatter (HS) interactions from uninteresting pileup (PU) interactions in a spatially compact environment. This problem becomes even harder to solve at higher luminosities. This project relies on leveraging the time dimension and determining a time of the HS intera

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Guan, Xiao. "Deterministic and Flexible Parallel Latent Feature Models Learning Framework for Probabilistic Knowledge Graph." Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-35788.

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Knowledge Graph is a rising topic in the field of Artificial Intelligence. As the current trend of knowledge representation, Knowledge graph research is utilizing the large knowledge base freely available on the internet. Knowledge graph also allows inspection, analysis, the reasoning of all knowledge in reality. To enable the ambitious idea of modeling the knowledge of the world, different theory and implementation emerges. Nowadays, we have the opportunity to use freely available information from Wikipedia and Wikidata. The thesis investigates and formulates a theory about learning from Know

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Long, Yangjing. "Graph Relations and Constrained Homomorphism Partial Orders." Doctoral thesis, Universitätsbibliothek Leipzig, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-154281.

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We consider constrained variants of graph homomorphisms such as embeddings, monomorphisms, full homomorphisms, surjective homomorpshims, and locally constrained homomorphisms. We also introduce a new variation on this theme which derives from relations between graphs and is related to multihomomorphisms. This gives a generalization of surjective homomorphisms and naturally leads to notions of R-retractions, R-cores, and R-cocores of graphs. Both \\mbox{R-cores} and R-cocores of graphs are unique up to isomorphism and can be computed in polynomial time. The theory of the graph homomorphism ord

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Domke, Jens. "Routing on the Channel Dependency Graph:." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-225902.

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In the pursuit for ever-increasing compute power, and with Moore's law slowly coming to an end, high-performance computing started to scale-out to larger systems. Alongside the increasing system size, the interconnection network is growing to accommodate and connect tens of thousands of compute nodes. These networks have a large influence on total cost, application performance, energy consumption, and overall system efficiency of the supercomputer. Unfortunately, state-of-the-art routing algorithms, which define the packet paths through the network, do not utilize this important resource effic

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Karam, Zahi Nadim. "Subspace and graph methods to leverage auxiliary data for limited target data multi-class classification, applied to speaker verification." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/66009.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 127-130).<br>Multi-class classification can be adversely affected by the absence of sufficient target (in-class) instances for training. Such cases arise in face recognition, speaker verification, and document classification, among others. Auxiliary data-sets, which contain a diverse sampling of non-target instances, are leveraged in this thesis using subspace and graph methods to improve classifi

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Gross, Brandi Nicole. "Input of Factor Graphs into the Detection, Classification, and Localization Chain and Continuous Active SONAR in Undersea Vehicles." Thesis, Virginia Tech, 2015. http://hdl.handle.net/10919/56609.

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The focus of this thesis is to implement factor graphs into the problem of detection, classification, and localization (DCL) of underwater objects using active SOund Navigation And Ranging (SONAR). A factor graph is a bipartite graphical representation of the decomposition of a particular function. Messages are passed along the edges connecting factor and variable nodes, on which, a message passing algorithm is applied to compute the posterior probabilities at a particular node. This thesis addresses two issues. In the first section, the formulation of factor graphs for each section of the

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Raveaux, Romain. "Fouille de graphes et classification de graphes : application à l’analyse de plans cadastraux." Thesis, La Rochelle, 2010. http://www.theses.fr/2010LAROS311/document.

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Les travaux présentés dans ce mémoire de thèse abordent sous différents angles très intéressants, un sujet vaste et ambitieux : l’interprétation de plans cadastraux couleurs.Dans ce contexte, notre approche se trouve à la confluence de différentes thématiques de recherche telles que le traitement du signal et des images, la reconnaissance de formes, l’intelligence artificielle et l’ingénierie des connaissances. En effet, si ces domaines scientifiques diffèrent dans leurs fondements, ils sont complémentaires et leurs apports respectifs sont indispensables pour la conception d’un système d’inter

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Lima, Mendez Gipsi. "Towards in silico detection and classification of prokaryotic Mobile Genetic Elements." Doctoral thesis, Universite Libre de Bruxelles, 2008. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210578.

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Bacteriophage genomes show pervasive mosaicism, indicating that horizontal gene exchange plays a crucial role in their evolution. Phage genomes represent unique combinations of modules, each of them with a different phylogenetic history. Thus, a web-like, rather than a hierarchical scheme is needed for an appropriate representation of phage evolutionary relationships. Part of the virology community has long recognized this fact and calls for changing the traditional taxonomy that classifies tailed phages according to the type of genetic materials and phage tail and head/capsid morphologies. Mo

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Ezzeddine, Diala. "A contribution to topological learning and its application in Social Networks." Thesis, Lyon 2, 2014. http://www.theses.fr/2014LYO22011/document.

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L'Apprentissage Supervisé est un domaine populaire de l'Apprentissage Automatique en progrès constant depuis plusieurs années. De nombreuses techniques ont été développées pour résoudre le problème de classification, mais, dans la plupart des cas, ces méthodes se basent sur la présence et le nombre de points d'une classe donnée dans des zones de l'espace que doit définir le classifieur. Á cause de cela la construction de ce classifieur est dépendante de la densité du nuage de points des données de départ. Dans cette thèse, nous montrons qu'utiliser la topologie des données peut être une bonne

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Dunn, Sarah, and Sean M. Wilkinson. "Increasing the resilience of air traffic networks using a network graph theory approach." Elsevier, 2015. https://publish.fid-move.qucosa.de/id/qucosa%3A72825.

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Air traffic networks are essential to today’s global society. They are the fastest means of transporting physical goods and people and are a major contributor to the globalisation of the world’s economy. This increasing reliance requires these networks to have high resilience; however, previous events show that they can be susceptible to natural hazards. We assess two strategies to improve the resilience of air traffic networks and show an adaptive reconfiguration strategy is superior to a permanent re-routing solution. We find that, if traffic networks have fixed air routes, the geographical

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Petzold, Maria. "Maximale Kantengewichte zusammenhängender Graphen." Doctoral thesis, Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola", 2012. http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-89030.

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Das Gewicht einer Kante e = xy eines Graphen G = (V, E) ist definiert als Summe der Grade seiner Endpunkte und das Gewicht des Graphen als MInimum über alle Kantengewichte. Wir suchen für positive ganze Zahlen n,m und eine Grapheneigenschaft P den Wert: w(n,m, P) := max{w(G) : |V(G)| = n, |E(G)| = m,G in P}. Der ungarische Mathematiker Erdös formulierte 1990 auf dem Czecheslovak Symposium on Combinatorics, Graphs and Complexity die Problemstellung w(n,m, I) zu bestimmen, für die allgemeinste aller Graphenklassen I. Dieses Problem wurde zuerst teilweise von Invančo and Jendrol’ und dann endgült

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Behmo, Régis. "Visual feature graphs and image recognition." Phd thesis, Ecole Centrale Paris, 2010. http://tel.archives-ouvertes.fr/tel-00545419.

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La problèmatique dont nous nous occupons dans cette thèse est la classification automatique d'images bidimensionnelles, ainsi que la détection d'objets génériques dans des images. Les avancées de ce champ de recherche contribuent à l'élaboration de systèmes intelligents, tels que des robots autonomes et la création d'un web sémantique. Dans ce contexte, la conception de représentations d'images et de classificateurs appropriés constituent des problèmes ambitieux. Notre travail de recherche fournit des solutions à ces deux problèmes, que sont la représentation et la classification d'images. Afi

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Reinwardt, Manja. "Combinatorial and graph theoretical aspects of two-edge connected reliability." Doctoral thesis, Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola", 2015. http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-184297.

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Die Untersuchung von Zuverlässigkeitsnetzwerken geht bis zum frühen 20. Jahrhundert zurück. Diese Arbeit beschäftigt sich hauptsächlich mit der Zweifach-Kantenzusammenhangswahrscheinlichkeit. Zuerst werden einfache Algorithmen, die aber für allgemeine Graphen nicht effizient sind, gezeigt, zusammen mit Reduktionen. Weiterhin werden Charakterisierungen von Kanten bezogen auf Wegemengen gezeigt. Neue strukturelle Bedingungen für diese werden vorgestellt. Neue Ergebnisse liegen ebenfalls für Graphen hoher Dichte und Symmetrie vor, genauer für vollständige und vollständig bipartite Graphen. Naturg

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Luqman, Muhammad Muzzamil. "Fuzzy multilevel graph embedding for recognition, indexing and retrieval of graphic document images." Thesis, Tours, 2012. http://www.theses.fr/2012TOUR4005/document.

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Cette thèse aborde le problème du manque de performance des outils exploitant des représentationsà base de graphes en reconnaissance des formes. Nous proposons de contribuer aux nouvellesméthodes proposant de tirer partie, à la fois, de la richesse des méthodes structurelles et de la rapidité des méthodes de reconnaissance de formes statistiques. Deux principales contributions sontprésentées dans ce manuscrit. La première correspond à la proposition d'une nouvelle méthode deprojection explicite de graphes procédant par analyse multi-facettes des graphes. Cette méthodeeffectue une caractérisati

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Douar, Brahim. "Fouille de sous-graphes fréquents à base d'arc consistance." Thesis, Montpellier 2, 2012. http://www.theses.fr/2012MON20108/document.

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Avec la croissance importante du besoin d'analyser une grande masse de données structurées tels que les composés chimiques, les structures de protéines ou même les réseaux sociaux, la fouille de sous-graphes fréquents est devenue un défi réel en matière de fouille de données. Ceci est étroitement lié à leur nombre exponentiel ainsi qu'à la NP-complétude du problème d'isomorphisme d'un sous-graphe général. Face à cette complexité, et pour gérer cette taille importante de l'espace de recherche, les méthodes classiques de fouille de graphes ont exploré des heuristiques de recherche basées sur le

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Grieshaber, Frank. "GODOT: graph of dated objects and texts: building a chronological gazetteer for antiquity." Epigraphy Edit-a-thon : editing chronological and geographic data in ancient inscriptions ; April 20-22, 2016 / edited by Monica Berti. Leipzig, 2016. Beitrag 6, 2016. https://ul.qucosa.de/id/qucosa%3A15468.

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