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 13 of 13 for “"Label Propagation"”.
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Fast Partitioning for Distributed Graph Learning using Multi-level Label Propagation
… this goal, I design and implement a hierarchical label-propagation-based graph partitioning system known as PLaTE (Propagating Labels to Train Efficiently), partially based on the paper “How to Partition a Billion Node Graph” [18]. PLaTE runs 5.6x faster than METIS on the Open Graph Benchmark’s …
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Robust graph transduction
… graph, graph transduction aims to assign unlabeled examples explicit class labels rather than build a general decision function based on the available labeled examples. Practically, a dataset usually contains many noisy data, such as the “bridge points” located across different classes, and …
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Deep Learning-Based Part Labeling of Tree Components in Point Cloud Data
… algorithms and pipelines for segmentation and labeling of tree components. This thesis presents a novel pipeline that employs deep learning models, such as the Point-Voxel Transformer (PVT), and synthetic tree point clouds for automatic tree part-segmentation. The pipeline leverages the …
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Benchmarking Methods For Predicting Phenotype Gene Associations
… in human diseases. Computational methods such as label-propagation and supervised-learning address challenges posed by traditional approaches such as manual curation to link genes to phenotypes in the HPO. It is only in recent years that computational methods have been applied in a network-based …
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Overlapping communities on social networks : a self-falsifiable hierarchical detection algorithm
… community detection based on an advanced label propagation process, which imitates the community formation process on social networks. Our algorithm is parameter-free and is able to reveal the hierarchical order of communities in the graph. The unique property of our solution scheme is …
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Local selection of features and its applications to image search and annotation
… of neighboring objects that share the same class label as the query object, is crucial for many applications, such as content-based image retrieval and automated image annotation. However, due to the existence of noisy or irrelevant features, errors introduced into similarity measurements are …
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eMicro: Real-Time Multi-Hop Access Control for Microservices with eBPF
… supporting constant-time lookups and compact label propagation; (3) eBPF-based in-kernel request tracing for transparent, low-overhead enforcement without code changes. Evaluations on DeathStarBench and production cloud traces from Uber, Alibaba, and ByteDance, covering 12 million request …
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A Unified Multiscale Encoder-Decoder Transformer for Video Segmentation
… learning scheme that exploits many-to-label propagation across time. To demonstrate the applicability of the approach, we provide empirical evaluation of MED-VT/MEDVT++ on three unimodal video segmentation tasks: (Automatic Video Object Segmentation (AVOS), actor-action segmentation, …
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An improved framework for content and link-based web spam detection: a combined approach
… as content-based features, link-based features, label propagation, label refinement, click-based web spamming detection, and real-time web spam detection. However, identifying all spam pages on the Web with high accuracy is still remains unsolved. This work proposes a content-based web spam …
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Graph-based approaches for semi-supervised and cross-domain sentiment analysis
… One of the main problems is the lack of labelled data necessary to carry out precise supervised sentiment classi cation. In response, research has moved towards developing semi-supervised and crossdomain techniques. Semi-supervised approaches still need some labelled data and their e …
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Context Driven Scene Understanding
… locate it with a bounding box or pixel-wise labels. In this dissertation, we present context driven approaches leveraging relationships between objects in the scene to improve both the accuracy and efficiency of scene understanding. In the first part, we describe an approach to jointly solve …
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Advanced Deep Learning Methods for the Automatic Analysis of Radar Sounder Data
… of the data and the limited availability of labeled examples. While Deep Learning (DL) has revolutionized image analysis in many domains, its application to RS is limited by the scarcity of labeled data, the presence of different noise sources, and the uncommon characteristics of the data. …
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PATIENT SIMILARITY NETWORKS-BASED METHODS FOR MULTIMODAL DATA INTEGRATION AND CLINICAL OUTCOME PREDICTION
… learning algorithms (i.e. Random Forests, label propagation and guilt-by-association), thus being potentially used to integrate datasets having unlabeled patients that are common in multi-omics datasets. To the best of our knowledge, this is the first time that a multimodal integration …