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 52 for “"Tabular 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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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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BayesDB : querying the probable implications of tabular data
BayesDB, a Bayesian database table, lets users query the probable implications of their tabular data as easily as an SQL database lets them query the data itself. Using the built-in Bayesian Query Language (BQL), users with little statistics knowledge can solve basic data science problems, such as …
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End-User Customization by Direct Manipulation of Tabular Data
… scripts in a programming language. We introduce data-driven customization, a new way for end users to extend software by direct manipulation without doing traditional programming. We augment existing user interfaces with a table view showing the structured data inside the application. When users …
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A Topology-Guided Diffusion Process for Synthetic Tabular Data Generation
Synthesizing realistic tabular data is crucial for any analytical application, including policy evaluation related to household energy use. However, detailed household-level consumption data, necessary for such evaluation, are scare at fine geographic scales, as public surveys like the U.S. …
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Advances in Few-Shot Learning for Image Classification and Tabular Data
… learning systems frequently operate in dynamic, data-scarce environments where assembling large labelled datasets is infeasible or impractical. Key examples include personalisation, federated learning, and privacy-sensitive applications -- each requiring robust learning from minimal data. These …
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Design and Evaluation of an AI-Driven Pipeline for Synthetic Tabular Data Generation
The increasing reliance on cloud environments for data-driven applications has created a critical tension between operational efficiency and regulatory compliance. Organisations require high-quality, representative data for effective software testing, but traditional Test Data Management (TDM) …
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Synthesizing Tabular Time Series Data using Transformers
Using synthetic data in place of real data can come with numerous benefits, such as the protection of privacy. However, synthesizing tabular data is difficult, since it is heterogeneous and might contain relationships between its columns and between its rows. While there has been much work …
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Towards Creating Synthetic Data Testbeds for Research
Insurance datasets are generally private in order to protect user information, making it difficult for the ML research community to access and experiment with this data. To increase accessibility and innovation on private insurance data, we compile and share publicly available insurance datasets, …
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Layout Inference and Table Detection in Spreadsheet Documents
… functionalities. In this way, they can support data collection, transformation, analysis, and reporting. Nevertheless, at the same time spreadsheets maintain a friendly and intuitive interface. Additionally, they entail no to very low cost. Well-known spreadsheet applications, such as …
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DataSpread: scaling spreadsheets using relational databases
… software is the tool of choice for ad-hoc tabular data management, manipulation, querying, and visualization with adoption by billions of users. However, spreadsheets are not scalable, unlike database systems. We develop DataSpread, a system that holistically unifies databases and …
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Low-Energy Photon Dose Deposition in Tissue Slab and Spherical Phantoms
… plastic, lucite, water, and polystyrene. Tabular data are presented for 0.007, 0.3 and 1.0 g/cm('2) depths. Results are compared with calculations of other workers and with experimental data available for the tissue-substitute plastic.
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Multimodal learning and language models for enhanced knowledge representations
… processing, graph representation learning, and tabular data analysis. However, these successes have predominantly relied on abundant, single-modal datasets, often overlooking the inherently multimodal and structurally complex nature of real-world data. Real-world data typically combines multiple …
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STAR : a tool for finding relationships between traits in games
In this paper, we introduce a tool to transform tabular data into an interactive network map. Compared to previous visualization tools, ours allows for more customization in terms of datasets, connecting nodes, and appearance. We describe three use scenarios where the tool was effective in helping …
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Tabular Machine Learning on Small-Size and High-Dimensional Data
… models on small-size and high-dimensional tabular datasets. Tabular data – tables where each row represents an individual record and each column represents features – is ubiquitous in critical fields such as medicine, scientific research and finance. However, these areas often face data …
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A Transformer for scATAC-scRNA Translation
… theory missed by scRNA-seq. However, scATAC-seq data is highdimensional and noisy, aspects which when compounded with data scarcity present challenges for modeling on even seemingly-simple downstream tasks such as cell-type prediction. As such, researchers may benefit from access to a large …
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Developing an interactive overview for non-visual exploration of tabular numerical information
… of obtaining overview information from complex tabular numerical data sets non-visually. Blind and visually impaired people need to access and analyse numerical data, both in education and in professional occupations. Obtaining an overview is a necessary first step in data analysis, for which …
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Enhancing Cloud Database Performance: General-Purpose Compression and Workload-Driven Layout
Cloud-based disaggregated database systems that divide data across a data layer and a storage layer connected by network calls are popular for analytical query loads. This thesis explores two topics critical to building performant systems of this type: space optimization and latency minimization. …
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Eliciting Expert Uncertainty from Decision Making
… an analyst to model expert decision-making data to elicit a probability distribution that reflects expert uncertainty. An example of parole board decision-making is used to elicit a prior distribution of a prisoner re-offending upon release from prison. This example shows analysts how to …
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