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 37 for “"synthetic data generation"”.
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Differentially Private Synthetic Data Generation for Relational Databases
Existing differentially private (DP) synthetic data generation mechanisms typically assume a single-source table. In practice, data is often distributed across multiple tables with relationships across tables. This study presents the first-of-its-kind algorithm that can be combined with \emph{any} …
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SDV : an open source library for synthetic data generation
… a robust system that can accurately generate synthetic data. The goals of this thesis were to separate the different components in synthetic data generation into their own libraries. We identified these components as consisting of a way to transform the data, a way to model the data, and a way …
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Design and development of an LLM-based framework for synthetic data generation
The increasing demand for high-quality datasets in fields such as healthcare, finance, and cybersecurity is hindered by challenges such as data scarcity, privacy concerns, and regulatory restrictions. This thesis introduces a novel framework for generating synthetic data using fine-tuned Large …
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WiSDM: a platform for crowd-sourced data acquisition, analytics, and synthetic data generation
… a result, it is desirable to collect behavioral data before and during a disease outbreak. Such data can help in creating better computer models that can, in turn, be used by epidemiologists and policy makers to better plan and respond to infectious disease outbreaks. However, traditional data …
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Synthetic data generation pipeline to effectively train deep learning augmented super-resolution ultrasound imaging
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-05-01
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Synthetic Data Generation and Sampling for Online Training of DNN in Manufacturing Supervised Learning Problems
… of Industrial Internet offers abundant passive data from manufacturing systems and networks, which enables data-driven modeling with high-data-demand, advanced statistical models such as Deep Neural Networks (DNNs). Deep Neural Networks (DNNs) have proven to be remarkably effective in supervised …
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Design and Development of a Chatbot as an Alternative Web-browser for those with Severe Motor Impairments
… access to online information, and (2) a synthetic data generation approach to improve voice-based chatbot systems’ ability to interpret atypical speech. First, an empirical study involving 20 participants established optimal parameters for eye-gaze target interaction in an Augmented …
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Visualization and Behavioral Testing Of Common Sense Generative Programs
… area. Specifically, I present a pipeline for synthetic data generation with physics simulation capabilities and a suite of rendering options. By leveraging existing scene graph generators and multiple visualization engines, photorealistic datasets can be produced to evaluate probabilistic …
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Investigation of machine learning tools for document clustering and classification
Data clustering is a problem of discovering the underlying data structure without any prior information about the data. The focus of this thesis is to evaluate a few of the modern clustering algorithms in order to determine their performance in adverse conditions. Synthetic Data Generation software …
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Synthesizing Linked Data and Detecting Per-Query Gaps Under Differential Privacy
<p>The abundance of data, often containing private and sensitive information, coupled with an ever-growing interest in using the data for research and driving business value at scale has raised concerns about privacy protections. Formal policies have made access to such data heavily regulated, …
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A GAN-Augmented Machine Learning Framework for Predicting Raman Characteristics in Carbon Nanofiber Synthesis
This thesis explores a hybrid data-driven framework for predicting the structural quality of Carbon Nanofibers (CNFs) synthesized via Chemical Vapor Deposition (CVD). Building upon prior work employing Conditional Tabular GAN (CTGAN) for data augmentation and XGBoost for quality prediction, this …
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New Approaches to Synthetic Tabular Data Generation
Synthetic data generation, while already becoming well-known as part of Generative AI (GenAI), has been primarily focused on images, voice, and text, which mostly have homogeneous data formats. This dissertation focuses on the modeling and generation of synthetic tables, which involve a range of …
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Early Diagnosis and Personalised Treatment: Classification Modelling of Immunotherapy Data Utilising Machine Learning and Deep Learning
… immunotherapy faces obstacles as medical data are typically small, imbalanced and contain irrelevant features, resulting in suboptimal classification performance. Therefore, the following contributions are proposed, addressing the data challenges. A comprehensive immunotherapy literature …
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Geometrical Models for 2D Morphometry in Bioimages
… and illustrate its use in the context of synthetic data generation.
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Privacy-Preserving Synthetic Medical Data Generation with Deep Learning
… Language Processing. However, the utilization of data-driven methods in healthcare raises privacy concerns, which creates limitations for collaborative research. A remedy to this problem is to generate and employ synthetic data to address privacy concerns. Existing methods for artificial data …
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Synthesizing tabular data using conditional GAN
In data science, the ability to model the distribution of rows in tabular data and generate realistic synthetic data enables various important applications including data compression, data disclosure, and privacy-preserving machine learning. However, because tabular data usually contains a mix of …
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The Synthetic Data Vault : generative modeling for relational databases
… is to build a system that automatically creates synthetic data for enabling data science endeavors. To meet this goal, we present the Synthetic Data Vault (SDV), a system that builds generative models of relational databases. We are able to sample from the model and create synthetic data, hence …
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Image-based pose estimation of sub-centimeter industrial parts for robotic grasping
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-03-28 without embargo terms
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Optimizing Machine Learning Performance on Tabular Clinical Data: A Pipeline Approach
… solutions for mixed-type tabular clinical data. Such datasets, prevalent in healthcare, are characterized by a complex interplay of numerical and categorical features, often leading to intricate, non-linear dependencies that hinder traditional analysis and model efficacy. Confronting …
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