Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 79 for “"random graph"”.
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Local-access generators for basic random graph models
Consider a computation on a massive random graph: Does one need to generate the whole random graph up front, prior to performing the computation? Or, is it possible to provide an oracle to answer queries to the random graph "on-the-fly" in a much more efficient manner overall? That is, to provide a …
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Inferring differences between networks using Bayesian exponential random graph models
… for populations of networks based on exponential random graph models. By pooling information across the individual networks, this framework provides a principled approach to characterise the relational structure for an entire population. We use the framework to assess group-level variations in …
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The use of exponential random graph models to explore social foraging dynamics of interspecific songbird assemblages
… testing. One such advance is exponential random graph models (ERGMs). Developed for the social sciences, ERGMs analyze how network structures (i.e., configurations of edges) and attributes of nodes and edges affect the formation of edges. This allows practitioners to explore how different …
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Bayesian multiple-network multi-layer exponential random graph models (MNML-ERGMs): developing efficient inference and application to neuroimaging
… a single binary network. The exponential random graph model (ERGM) belongs to such models, which characterise the distribution of networks through a set of network summary statistics. Each summary statistic provides a topological summary of a network, and ERGM is empowered by its …
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Exponential Random Graphs and a Generalization of Parking Functions
<p>Random graphs are a powerful tool in the analysis of modern networks. Exponential random graph models provide a framework that allows one to encode desirable subgraph features directly into the probability measure. Using the theory of graph limits pioneered by Borgs et. al. as a foundation, we …
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Classification of Countable Homogeneous 2-Graphs
We classify certain families of homogeneous 2-graphs and prove some results that apply to families of 2-graphs that we have not completely classified. We classify homogeneous 2-coloured 2-graphs where one component is a disjoint union of complete graphs and the other is the random graph or the …
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Dynamic Reconfiguration of Network Topology in Optical Networks
… demand matrix. To implement the MRAS method a random graph generation algorithm is needed. To address this need, a very efficient random graph generation algorithm is developed that competes with existing algorithms in the literature.
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High-dimensional and dependent data with additional structure
… multivariate time series and exponential-family random graph models. In the case of high-dimensional multivariate time series, there is often additional structure in the form of spatial structure, e.g., air pollution is monitored by monitors and the geographical locations of monitors are known. …
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Resource Management for Real -Time Environments
We make connections with random graph theory and statistical physics and show specific instances where we can solve problems that were hitherto hard to solve or improve the results for some well-studied problems. The instances that we study are: phased-array radar dwell scheduling, multiprocessor …
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Topics In Probabilistic Combinatorics
… basic definitions, lemmas, and theorems from graph theory, asymptotic analysis, and probability which will be used throughout the paper. Chapter 2 introduces the independent domination number. It is then shown that in the random graph model G(n,p) with probability tending to one, the …
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Analyzing The Community Structure Of Web-like Networks: Models And Algorithms
… structure of web-like networks (i.e., large, random, real-life networks such as the World Wide Web and the Internet). Recently, it has been shown that many such networks have a locally dense and globally sparse structure with certain small, dense subgraphs occurring much more frequently than …
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The Cover Time of Random Walks on Graph
A simple random walk on a graph is a sequence of movements from one vertex to another where at each step an edge is chosen uniformly at random from the set of edges incident on the current vertex, and then transitioned to next vertex. Central to this thesis is the cover time of the walk, that is, …
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Phase transition for cutoff for random walks on random graphs
… analyse the cutoff phenomenon on two different random graph models. First, we consider a variant of the configuration model with an embedded community structure and study the mixing properties of a simple random walk on it. Every vertex has a given number of internal, degint ≥ 3, and outgoing, …
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Channel Comparison Methods and Statistical Problems on Graphs
… these tools to statistical problems related to graphs. Part I focuses on information channels and channel comparison methods, including f-divergences, strong data processing inequalities, and preorders between channels. While these theories have been well-established for binary memoryless …
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Generating Random Graphs with Tunable Clustering Coefficient
… at a node) as input and generate a random graph with a tunable clustering coefficient. We analyze them theoretically and empirically for the case of a regular graph. CONF-1 and CONF-2 generate a random graph with the degree sequence and the clustering coefficient anticipated from the …
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Using Graph Clustering to Analyze the Spread of an Infectious Disease on a Random Large Social Network Graph
… analyze the spread of an infectious disease on a random large social network graph. The goal is to determine if graph clustering techniques are a viable option to reduce workload of analyzing of a large data set. A random graph generator was developed using characteristics from the Forest Fire …
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Variational approximation for importance sampling and statistical inference on social influence
… In the third part of the thesis, we propose a random graph model for undirected networks with small-world properties, namely with a high clustering coefficient and a low average path length. We generalize the regular Erd\H{o}s-R\'enyi dyadic random graph by considering higher-order motif, which …
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Direct Computations of Spatially Resolved Viscoelastic Moduli of Biomolecular Condensates
… In this study, we develop a modified graph Laplacian-based collective model to characterize viscoelastic heterogeneity within condensates based on results of lattice-based Metropolis Monte Carlo (MMC) simulations. By integrating random graph models and simulations of A1-LCD, a type of …
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Design, analysis and reconfiguration of defect-tolerant VLSI and parallel processor arrays
… array reconfiguration problem is formulated as a random graph problem, and a provably average-case polynomial time algorithm is presented, while all previous memory reconfiguration algorithms were given without an average-case time complexity analysis. The implemented algorithm runs faster than …
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Structure and evolution of communication networks in organizations
… networks in an organization differ from random networks and other social networks. We also compare and contrast the three types of communication networks. Using Quadratic Assignment Procedure (QAP), Multiple Regression Quadratic Assignment Procedure (MRQAP) and Exponential Random Graph …
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