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 43 for “"Graph partitioning"”.
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FPGA-based implementation of parallel graph partitioning
Graph partitioning is a very important application that can be found in numerous areas, from finite element methods to data processing and VLSI circuit design. Many algorithms have been developed to solve this problem. Of special interest is multilevel graph partitioning that provides a very …
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0-1 graph partitioning and image segmentation
Graph partitioning is the grouping of all the nodes in a graph into two or more partitions based on certain criteria. Graph cut techniques are used to partition a graph. The Minimum Cut method gives imbalanced partitions. To overcome the imbalanced partitioning, the Normalized Cut method is used. …
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Optimization approaches for political districting and graph partitioning
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms
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Algorithms for new objectives in graph partitioning and generalizations
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms
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Graph partitioning: redistricting games and the spherical zoning problem
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-08-01
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New geometric techniques for linear programming and graph partitioning
… of linear programming, polytope theory, spectral graph theory, and graph partitioning. The thesis consists of two main parts. In the first part, which is joint work with Daniel Spielman, we present the first randomized polynomial-time simplex algorithm for linear programming, answering a question …
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Thanos: High-performance CPU-GPU based balanced graph partitioning using cross-decomposition
As graphs become larger and more complex, it is becoming nearly impossible to process them without graph partitioning. Graph partitioning creates many subgraphs which can be processed in parallel thus delivering high-speed computation results. However, graph partitioning is a difficult task. In …
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New Differential Zone Protection Scheme Using Graph Partitioning for an Islanded Microgrid
… new differential zone protection scheme using a graph partitioning algorithm. A graph partitioning algorithm is used to partition the microgrid into multiple protective zones. The IEEE 13-node microgrid is used to demonstrate the proposed protection scheme. The protection scheme is validated with …
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A study of graph partitioning techniques for fast indexing and query processing of a large RDF graph
… The collection of triples together represents a graph. Many techniques have been developed for RDF indexing and query processing and the most popular among them store and process RDF data using an RDBMS. In this thesis, we study the impact of existing graph partitioning techniques on indexing and …
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Multilevel spectral clustering : graph partitions and image segmentation
While the spectral graph partitioning method gives high quality segmentation, segmenting large graphs by the spectral method is computationally expensive. Numerous multilevel graph partitioning algorithms are proposed to reduce the segmentation time for the spectral partition of large graphs. …
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A low-cost design of multiservice SDH networks with multiple constraints
… delay. The problem is characterized as a graph-partitioning problem, and a heuristic algorithm based on constraints programming satisfaction technology is proposed.
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Fast Partitioning for Distributed Graph Learning using Multi-level Label Propagation
Graph Neural Networks (GNNs) are a popular class of machine learning models that allow scientists to leverage machine learning techniques to perform inference on unstructured data. However, when graphs become too large, partitioning becomes necessary to allow for distributed computation. Standard …
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Piecewise truckload network procurement
… the sizes of each bid, and is framed as a graph partitioning problem. The second treats lanes as independent entities and frames network allocation as a bin-packing problem, with constraints that attempt to achieve both balance and, implicitly, synergy preservation. These two approaches are …
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Ordering Strategies for Sparse Matrices in Chemical Process Simulation
… investigated include local heuristic strategies, graph, partitioning techniques, and iterative methods. These methods were compared with previously used orderings, in terms of structural criteria, solution time, and parallel speedup. For the one processor frontal method, the local heuristic …
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Vertex sparsification and universal rounding algorithms
… (because our algorithms run on a much smaller graph). Additionally, we apply these ideas to obtain a master theorem for graph partitioning problems - as long as the integrality gap of a standard linear programming relaxation is bounded on trees, then the integrality gap is at most a logarithmic …
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Image segmentation in the wavelet domain using N-cut framework
… from the wavelet-transformed images to solve graph partitioning more efficiently than before. Five orientation histograms are computed to evaluate similarity/dissimilarity measure of local structure. We use properties of the wavelet transform filtering to capture edge information in vertical, …
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Minimum cut model for spoken lecture segmentation
… We re-conceptualize text segmentation as a graph-partitioning task aiming to optimize the normalized-cut criterion. Central to this framework is a contrastive analysis of lexical distribution that simultaneously optimizes the total similarity within each segment and dissimilarity across …
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Topology-aware distributed graph processing for tightly-coupled clusters
… machine learning systems called distributed graph processing systems, and run them on NCSA Blue Waters. Partitioning the graph is key to achieving performance in distributed graph processing systems. We present new topology-aware partitioning techniques that better exploit the structure of …
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The GraphGrind Framework: Fast Graph Analytics on Large Shared-Memory Systems
… they provide an opportunity to perform efficient graph analytics on a single machine. Graph analytics is characterised by frequent synchronisation, which is addressed in part by shared memory systems. However, performance is limited by load imbalance and poor memory locality, which originate in …
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Dynamic-parinet (D-parinet) : indexing present and future trajectories in networks
… of PARINET is based on a combination of graph partitioning and a set of composite B+-tree local indexes tuned for a given query load and a given data distribution in the network space. D-PARINET studies continuous update of trajectory data and use interpolation to predict future MO …
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