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.
Results
Showing 1 to 20 of 22 for “"Network embedding"”.
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Event network embedding
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-12-01
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An Evaluation Methodology for Virtual Network Embedding
The increasing scale and complexity of computer networks imposes a need for highly flexible management mechanisms. The concept of network virtualization promises to provide this flexibility. Multiple arbitrary virtual networks can be constructed on top of a single substrate network. This allows …
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Tensor Methods for Signal Reconstruction and Network Embedding
… representation of entities in multi-dimensional networks? How do we develop efficient lightweight algorithms that handle very large data? These are important questions that have risen on the top of the scientific and engineering agenda of ML and SP communities. A plethora of methods has been …
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Relation2vec: Contextualized network embedding for heterogeneous information networks
From biology to sociology, network theory has been used as a tool for modeling the relationships among entities in complex systems. However, with the emergence of big data, applying the conventional network analysis algorithms, which are often combinatorial, to the contemporary networks is …
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Trust-aware virtual network embedding algorithms for wireless sensor networks
Network virtualization (NV) in wireless sensor networks (WSNs) enables the utilization of their shared sensing capabilities. Efficient assignment of WSN resources to maximize the infrastructure provider’s revenue can be achieved by virtual network embedding (VNE) while considering the quality of …
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Evaluation study of virtual network embedding for short-lived virtual networks
… on physical or hardware infrastructure. Network virtualization is a recent advancement in this field through which virtual networks can be created over real physical networks (also called as substrate networks). Such virtual networks facilitate testing and quick deployment of new …
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Curriculum learning for heterogeneous star network embedding via deep reinforcement learning
Learning node representations for networks has attracted much attention recently due to its effectiveness in a variety of applications. This paper focuses on learning node representations for heterogeneous star networks, which have a center node type linked with multiple attribute node types …
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Mine the node association: Dig into the essence of graphs
… example, competing sampling strategies exist in network embedding based algorithms (e.g., the distant positive sampling strategy, and close negative sampling strategy). Third (the graph challenge), almost any real graph keeps evolving. How to capture the evolution pattern of node association and …
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Efficient embeddings of meshes and hypercubes on a group of future network architectures.
… structures used in parallel computing. Network embedding problems for meshes and hypercubes on traditional network architectures have been intensively studied during the past years. With the emergence of new network architectures, the traditional network embedding results are not enough …
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Interpretable Network Representations
<p>Networks (or interchangeably graphs) have been ubiquitous across the globe and within science and engineering: social networks, collaboration networks, protein-protein interaction networks, infrastructure networks, among many others. Machine learning on graphs, especially network representation …
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Fully Hyperbolic Graph Convolutional Neural Networks for Age Prediction with Multi-Modal Brain Data
… age-related alterations in MEG brain networks holds great promise in understanding aging trajectories and revealing aberrant patterns of neurodegenerative disorders, such as Alzheimer’s disease. In this study, we utilize a Fully Hyperbolic Neural Network (FHNN) to embed functional …
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Harnessing heterogeneous association in real-world networks
Real-world networks often contain heterogeneity due to the heterogeneous nature of the world. A few examples of such networks include multi-view social networks, heterogeneous bibliographic networks, biomedical networks, etc. Ostensibly the heterogeneity of real-world network appears as the typed …
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Evolving Network Representation Learning Based on Random Walks
Large-scale network mining and analysis is key to revealing the underlying dynamics of networks, not easily observable before. Lately, there is a fast-growing interest in learning low-dimensional continuous representations of networks that can be utilized to perform highly accurate and scalable …
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Representation Learning on Large-Scale Neural and Healthcare Data: A Practitioner’s Perspective
… records (EHR) using a collection of graph-based network embedding algorithms. The proposed framework can bring a number of advantages such as enhanced clinical outcome prediction accuracies and more interpretable modeling of patient medical profiles and treatment history, which suggest the …
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Achieving Differential Privacy and Fairness in Machine Learning
… and emerging tasks of causal graph discovery and network embedding, respectively.</p> <p>(2) We develop the fair generative adversarial neural networks framework and three algorithms (FairGAN, FairGAN+ and CFGAN) to achieve fair data generation and classification through generative models based on …
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Approximate likelihood for dependent networks and hyperlink predictions
Network data has arisen as one of the most common forms of information collection. This is due to the fact that the scope of studies not only focuses on subjects alone, but also on the relationships among subjects. In this thesis, we address two major challenges in the network analysis. In the …
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Performance and optimization technologies for software defined industrial networks
The concept of programmable networks is radically changing the way communication infrastructures are designed, integrated, and operated. Currently, the topic is spearheaded by concepts such as software-defined networking, forwarding and control element separation, and network function …
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Multi-objective Network Virtualization and its Applicability to Industrial Networks
Network virtualization provides high flexibility for deploying communication services in dense and heterogeneous environments. Two main approaches (dimensions) that are usually combined exist: Network Function Virtualization (NFV) technologies for functionality virtualization and Virtual Network …
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Constructing and modeling text-rich information networks: a phrase mining-based approach
… an organized heterogeneous information network, and developing powerful modeling mechanisms on such organized network. We name it text-rich information network, since it is an integrated representation of both structured and unstructured textual data. To thoroughly develop the …
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Efficient visualization for large-scale and high-dimensional single-cell data
… between single cells. We first construct a network that can represent the similarity structure between the high-dimensional representations of single cells, and then embed this network into a low-dimensional space through an efficient online optimization method based on the idea of negative …
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