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 92 for “"Data-Centric"”.
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Data-Centric Business Transformation
… the enterprises to effectively use vast amount data in order to gain critical business insights to stay competitive. In their aim to take advantage of data many large organizations are launching data management programs. In these attempts organizations recognize that taking full advantage of …
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Data Centric Defenses for Privacy Attacks
… to extract sensitive information about the data used in model training. These attacks called privacy attacks, exploit the model training process. Contemporary defense techniques make alterations to the training algorithm. Such defenses are computationally expensive, cause a noticeable …
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Data-centric Approaches for Responsible Data Science
The abundance of data, coupled with recent advancements in computation, has revolutionized almost every aspect of human life. While the undeniable benefits of this evolution are evident and despite the promise to bring good to human life and society, data-driven technologies could instead become …
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Data-Centric Machine Learning for Speech and Audio
… is growing recognition of the importance of data-centric methods for building machine learning systems. Data-centric methods assume a fixed model and iterate over the data to improve system performance. This is in contrast to traditional model-centric approaches, which assume a fixed dataset …
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Formal Specification and Verification of Data-Centric Web Services
… a formal model and contracting framework for data-centric Web services. The central component of our framework is a formal specification of a common Create-Read-Update-Delete (CRUD) data store. We show how this model can be used in the formal specification and verification of both basic and …
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On Reputation and Data-centric Misbehavior Detection Mechanisms for VANET
Vehicular ad hoc networks (VANET) is a class of ad hoc networks build to ensure the safety of traffic. This is important because accidents claim many lives. Trust and security remain a major concern in VANET since a simple mistake can have catastrophic consequence. A crucial point in VANET is how …
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TOWARDS RELIABLE AI UNDER DISTRIBUTION SHIFTS: A DATA-CENTRIC PERSPECTIVE
… rely on spurious correlations in the training data, leading to performance degradation and unreliability when processing inputs under distribution shifts. This thesis systematically studies the robustness to distribution shifts for ML models from a data-centric perspective. First, we closely …
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Data-Centric Situational Awareness and Management in Intelligent Power Systems
… system than ever. The request for big data based situation awareness and management becomes urgent today. In this dissertation, to respond to the grand challenge, two data-centric power system situation awareness and management approaches are proposed to address the security problems in …
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ScaleGPS: Scalable Graph Parallel Sampling via Data-centric Performance Engineering
… such as graph machine learning and graph data mining. However, because of unstructured sparsity in the graph data and the randomness in the sampling algorithms, graph sampling often is the computational bottleneck. To accelerate it, there exist parallel graph sampling methods on multicore …
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User interfaces supporting casual data-centric interactions on the Web
Today's Web is full of structured data, but much of it is transmitted in natural language text or binary images that are not conducive to further machine processing by the time it reaches the user's web browser. Consequently, casual users-those without programming skills-are limited to whatever …
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Understanding and Mitigating Data-Centric Vulnerabilities in Modern AI Systems
… (AI) systems, trained on vast internet-scale datasets, demonstrate remarkable performance and emergent capabilities. However, this reliance on large datasets that are expensive or difficult to quality-control exposes AI systems to critical vulnerabilities, including data poisoning, backdoor …
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Workload-aware compressed linear algebra for data-centric machine learning pipelines
Compression is an effective technique for fitting data in available memory, reducing I/O across the storage-memory-cache hierarchy, decreasing energy consumption, and increasing instruction parallelism. Modern machine learning (ML) systems exploit the approximate nature of ML and mostly use lossy …
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Data-centric methods for optimization and pattern discovery in networked systems
In this thesis, we examine two data-driven solutions to problems in operational networks. The first problem is concerned with assessing the resilience of the US air transportation network from an operational perspective. As a complex network comprising over 5,000 public airports and countless …
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A Data-Centric Approach to Loss Mechanisms for Compressor Preliminary Design
… physical patterns in complex multidimensional data. Detecting patterns in complex multidimensional data is exactly the task for which machine learning and other statistical techniques have been developed. The aim of this thesis, therefore, is to try and use machine learning to augment the human …
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Zephyr: a Data-Centric Framework for Predictive Maintenance of Wind Turbines
… energy assets. Manual analysis of wind turbine data is difficult and time-consuming due to its volume, variety, and, most importantly, the need for quick detection of issues. Machine learning (ML) methods are able to automate large-scale data analysis. However, the enormous amount of contextual …
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Enhancing a Data-Centric Framework for Predictive Maintenance of Wind Turbines
… and reliance on black-box models. Zephyr, a data-centric machine learning framework, addresses these challenges by enabling Subject Matter Experts (SMEs) to incorporate their domain knowledge into the prediction process, and to leverage automated tools for labeling, feature engineering, and …
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Realising data-centric UAV autonomy through learning-based prediction and feedback integration
… logs to a deployable closed loop — that combines data-driven prediction, evolutionary optimisation, and classical feedback to deliver reliable and interpretable autonomy. A data-driven virtual UAV is learned from real flight data using a nonlinear autoregressive model with exogenous inputs (NARX). …
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Methods to Improve Applicability and Efficiency of Distributed Data-Centric Compute Frameworks
… depends on the insights they collect from their data repositories. Data repositories for such applications currently exceed exabytes and are rapidly increasing in size, as they collect data from varied sources - web applications, mobile phones, sensors and other connected devices. Distributed …
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Shifting Paradigms: Data-Centric Approach for Marine Statics Correction using Symmetric Autoencoding
… marine statics has been based on a model-centric paradigm. This paradigm involves a series of transformations between non-commensurate spaces: first, inversion from seismic data space to velocity model space and second, forward modeling from velocity model space to seismic data space. …
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GreenHDFS: data-centric and cyber-physical energy management system for big data clouds
Explosion in Big Data has led to a rapid increase in the popularity of Big Data analytics. With the increase in the sheer volume of data that needs to be stored and processed, storage and computing demands of the Big Data analytics workloads are growing exponentially, leading to a surge in …
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