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 36 for “"Data curation"”.
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Data curation with ontology functional dependences
Poor data quality has become a pervasive issue due to the increasing complexity and size of modern datasets. Functional dependencies have been used in existing cleaning solutions to model syntactic equivalence. They are not able to model semantic equivelence, however. We advance the state of data …
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Data curation for foundation model training
… driving innovation. Given that the amount of data available for training these models was often limited, research aimed on improving the way these relatively small amounts of data could be used. More recently, this focus has shifted from iteration on the algorithms to iteration on the data …
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EFFICIENT DATA CURATION AND UTILIZATION FOR DEEP LEARNING
… construction efficiency of large-scale vision datasets, aiming to reduce computational and annotation costs. We propose InfoBatch, an unbiased dynamic data pruning framework that losslessly accelerates training and saves 20–40% of computation across diverse vision tasks. To address dataset …
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Scientific Data Collections: Use in Scholarly Communication and Implications for Data Curation
… Networked connectivity, the availability of data in digital forms and the development of computing tools are helping to bring about changes in the way science is conducted and communicated. These changes are having an impact on the range of scientific production and communication activities, …
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Site-based data curation: bridging data collection protocols and curatorial processes at scientifically significant sites
… an abundance of important and highly valuable data. Yet, though sites are logical points for coordinating the curation of these data, their unique needs have been under supported. Previous studies have shown that two principal stakeholder groups – scientific researchers and local resource …
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Systematic Development of Healthcare AI: From Data Curation, Algorithm Optimization, Benchmark Design and Clinical Applications
… AI through four interconnected components: data curation, algorithm optimization, benchmark design, and clinical applications. The primary contribution of this thesis focuses on establishing a comprehensive pipeline for healthcare large language models (LLMs), spanning from data curation to …
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Incorporate Out-of-Vocabulary Words for Psycholinguistic Analysis using Social Media Texts - An OOV-aware Data Curation Process and a Hybrid Approach
… model. The first artifact is an OOV-aware data curation process that focuses on capturing and categorizing OOV words. The evaluation of the first artifact demonstrates that it can capture more OOV words and is useful in analyzing SMT. The second artifact is an OOV-aware hybrid approach that …
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ARDA : automatic relational data augmentation for machine learning
This thesis is motivated by two major trends in data science: easy access to tremendous amounts of unstructured data and the effectiveness of Machine Learning (ML) in data driven applications. As a result, there is a growing need to integrate ML models and data curation into a homogeneous system …
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Unsupervised Learning for Generative Scene Editing and Motion
… usually have the best performance, the amount of data curation and labeling that supervised datasets require makes it difficult to scale. On the other hand, unsupervised learning is more scalable, generalizable, and requires much less data curation, but is harder because it lacks a clear target …
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Curation and privacy in mobile application UI repositories
… interaction mining allows everyday interaction data to be mined for insights into the best performing design patterns, usability problems, and overall design trends. So far, this data has primarily come from automated application exploration or crowdworkers completing smartphone tasks as part of …
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Automated Finetuning via Sparse Autoencoders
… assembling high-quality instruction finetuning datasets with minimal human intervention, requiring only concise task descriptions rather than evaluation dataset distributions. Our empirical evaluations show that UnderstandTune consistently outperforms uninformed finetuning baselines across …
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Investigating the Use of Artificial Intelligence in Chest Radiography: Efficacy, Bias, and Lessons from the COVID-19 Pandemic
… resulted in unprecedented access to medical datasets. Large, novel public datasets were created, such as the National COVID-19 Chest Imaging Database (NCCID) in the UK and the Medical Imaging and Data Resource Center (MIDRC) in the US. Thousands of AI models have been developed to improve …
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Epigenetic modelling: DNA methylation and working towards model parameterisation
… of epigenetics and the study of a specific database. As part of the latter work, the role of curation is described, and a new knowledge management system, PathEpigen1 , is reported that is currently being developed for colon cancer in the Sci-Sym centre. The database deals with genetic and …
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Desvendando as percepções e práticas adotadas pelos pesquisadores dos programas de pós-graduação em Ecologia do nodeste brasileiro na gestão dos dados científicos
Based on the premise that data from scientific investigations are usually stored on the researchers’ computers, discarded or even lost when the results are published in articles, making it impossible to produce new investigations, the present study sought to uncover the perceptions and practices …
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The application of file identification, validation, and characterization tools in digital curation
… preservation and, by extension, long-term data curation. These actions are performed on data objects by humans or computers, in an attempt to identify the type of a given file, derive characterizing information that is specific to the file, and validate that the given file conforms to its …
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From purification, spectroscopy, and microscopy of carbon dots to synthesis modeling and AI-assisted spectral data extraction
… physical modeling, and AI-assisted data curation. Part A develops and applies rigorous purification and fractionation to disentangle bottom-up products of CD synthesis from confounding small molecules; it then combines ensemble spectroscopy with single-particle fluorescence (Eric …
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Untangling the complexity of nature: Machine-learning for accelerated life-sciences
… to identify patterns of interest in complex datasets. Yet, the impact of such methods remains limited in the broad context of life-sciences. This work optimizes the utility of ML to accelerate research of fundamental biological problems. First, we propose a paradigm shift from siloed data …
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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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On the Resource Efficiency of Language Models
… faces resource challenges in two dimensions: data efficiency and model efficiency. For post-training, LLMs face data curation challenges where high-quality labeled data is scarce and expensive to obtain, and data utilization challenges where existing methods fail to optimize model performance …
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Data expertise and service development in geoscience data centers and academic libraries
… on staff who need to manage large and complex data, design user services, and enable open access. One ramification is that research institutions are extending their services and staffing to address data management concerns. As more organizations extend their operations to research data, an …
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