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 158 for “"subgraph"”.
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Subgraph classification through neighborhood pooling
Subgraph classification is an emerging field in graph representation learning where the task is to classify a group of nodes (i.e., a subgraph) within a graph. Graph neural networks (GNNs) are the de facto solution for node, link, and graph-level tasks but fail to perform well on subgraph …
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Cohesive Subgraph Computation in Graphs
… data. Among them, mining and querying cohesive subgraph structure in massive networks is of great importance for a deeper understanding and better management of such networks. However, the massive graph volume and rapid evolution present huge challenges, which need highly efficient solutions. In …
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Approximating the maximum acyclic subgraph
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.
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Fast and Scalable Subgraph Learning
… do not support an emerging class of workloads: subgraph classification, which is increasingly common in real-world applications. Prior implementations address this gap by modifying both the data pipeline and the model architecture—but at the cost of composability, creating tightly coupled …
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Scalable subgraph representation learning through simplification
… prediction on graphs is a fundamental problem. Subgraph representation learning approaches (SGRLs), by transforming link prediction to graph classification on the subgraphs around the links, have achieved state-of-the-art performance in link prediction. However, SGRLs are computationally …
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Learning with Degree-Based Subgraph Estimation
Networks and their topologies are critical to nearly every aspect of modern life, with social networks governing human interactions and computer networks governing global information-flow. Network behavior is inherently structural, and thus modeling data from networks benefits from explicitly …
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Inducibility and Subgraph Density Problems in Graphs
… consider the number of (not necessarily induced) subgraphs of G that are isomorphic to F, while in others we only consider the induced subgraphs of G.
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Dense subgraph detection on multi-layered networks
Dense subgraph detection is a fundamental building block for a variety of applications. Most of the existing methods aim to discover dense subgraphs within a single network, or within a multi-view network consisting of a common set of nodes. However, many real-world applications can be better …
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A comprehensive and efficient framework for subgraph matching
… aims to develop a comprehensive and efficient subgraph matching framework to support graph analytic tasks. In the era of information technology, graphs, consisting of vertices and edges, are widely used to model real-world entities and their relationships, offering new opportunities to …
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High performance DFS-based subgraph enumeration on GPUs
Subgraph enumeration is an important problem in the field of Graph Analytics with numerous applications. The problem is provably NP-complete and requires sophisticated heuristics and highly efficient implementations to be feasible on problem sizes of realistic scales. Parallel solutions have shown …
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Enhancements in high performance subgraph enumeration on graphics processors
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-08-01
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MPrompt: A Pretraining-Prompting Scheme for Enhanced Fewshot Subgraph Classification
… in node-level and graph-level learning tasks, subgraph-level tasks are highly underexplored, and the potential of prompting remains unclear. This thesis fills this gap by exploring the prompting mechanism for subgraph classification, which is a much more challenging task as it requires …
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Towards unified biomedical modeling with subgraph mining and factorization algorithms
This dissertation applies subgraph mining and factorization algorithms to clinical narrative text, ICU physiologic time series and computational genomics. These algorithms aims to build clinical models that improve both prediction accuracy and interpretability, by exploring relational information …
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SPIRAL: Iterative Subgraph Expansion for Knowledge-Graph Based Retrieval-Augmented Generation
… that constructs compact, tree-shaped evidence subgraphs. This differs from previous work in its use of a trained, iterative policy network built on top of a prior over triples, delivering improved performance on multi-hop question answering tasks. Stage 1 trains a single-label GLASS-GNN on …
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Algoritmi avanzati per il Subgraph Isomorphism, Motif Discovery, e Graph Embedding su reti complesse
I grafi sono strumenti potenti nelle scienze computazionali, in grado di modellare relazioni complesse in ambiti come la bioinformatica, l'analisi delle reti sociali e la chimica computazionale. Questa tesi affronta sfide fondamentali nell'analisi dei grafi, con particolare riferimento al problema …
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A Forbidden Subgraph Characterization Problem and a Minimal-Element Subset of Universal Graph Classes
… paper we show that if each H_i has a forbidden subgraph characterization then the direct sum and join of these H_i also have forbidden subgraph characterizations. We provide various results which in many cases allow us to exactly determine the minimal forbidden subgraphs for such …
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Pretraining Table Embeddings for Knowledge Graph Based Provenance Systems
… this work examines the problem of provenance subgraph classification: given a coarser low-level provenance subgraph that is not easily digestible by humans, we want to annotate the subgraph with human readable labels describing the operations done on each data object. This work first involves …
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On the structure and evolution of protein interaction networks
… either exact counting (e.g. [MSOI+02]) or subgraph sampling (e.g. [BP06, KIMA04a, MZW05]). In this thesis we develop an algorithm to count all instances of a particular subgraph, which can be used to query whether a given subgraph is a significant motif. This method can be used to perform …
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PLANAR GRAPHS, BIPLANAR GRAPHS AND GRAPH THICKNESS
… and blue such that the red edges induce a planar subgraph and the blue edges induce a planar subgraph. In this thesis, we determine the smallest complete and complete bipartite graphs that are not biplanar.</p>
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Efficient structure search in large data sets
… the structure search in graph data and focus on subgraph matching over large data graphs, which extracts all subgraph isomorphic embeddings of a query graph q in a large data graph G. For the first time we address the issue of unpromising results by Cartesian products from "dissimilar" vertices. …
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