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 11 of 11 for “"Data-driven Algorithm"”.
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Automated Data-driven Algorithm and Mechanism Design in Online Advertising Markets
… and subsequently platforms run automated algorithms to procure ads on advertisers' behalf. While autobidding significantly simplifies and scales up ad procurement processes, it also brings about new challenges: for advertisers, the simplification to ad procurement comes at the cost of …
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Wavelet-based Dynamic Mode Decomposition in the Context of Extended Dynamic Mode Decomposition and Koopman Theory
Koopman theory is widely used for data-driven modeling of nonlinear dynamical systems. One of the well-known algorithms that stem from this approach is the Extended Dynamic Mode Decomposition (EDMD), a data-driven algorithm for uncontrolled systems. In this thesis, we will start by discussing the …
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Data-Driven Polynomial Chaos Expansions for Uncertainty Quantification
Uncertainties exist in both physics-based and data-driven models of systems. Understanding how system inputs affect a system output's uncertainty is essential to improve system outputs such as quality and productivity. Variance-based sensitivity analysis, which is widely used for uncertainty …
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Cortical thickness estimation of the proximal femur from multi-view dual-energy X-ray absorptiometry
… femur from multi-view DXA scans. First, a data-driven algorithm is designed, implemented and evaluated. It relies on a femoral B-spline template which can be deformed to fit an individual’s scans. In a series of experiments on the trochanteric regions of 120 proximal femurs, the algorithm’s …
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An Iterative LQR Method for Addressing Model Uncertainty in the Mars Entry Problem
… the atmospheric models and navigational data uncertainty for the nonlinear dynamics of hypersonic entry by applying an iterative Linear-Quadradic-Regulator (iLQR). iLQR is an efficient and powerful method for trajectory optimization derived from Differential Dynamic Programming (DDP) …
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Learning condition-specific networks
… cellular networks of genes from expression data. This dissertation first describes an unsupervised machine learning framework for inferring cellular networks using expression data from a single condition. Here cellular networks are represented as undirected probabilistic graphical models and …
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Dimension Reduction in Structured Dynamical Systems: Optimal-𝓗<sub>2</sub> Approximation, Data-Driven Balancing, and Real-Time Monitoring
… pertaining to the model-order reduction, data-driven reduced-order modeling, and real-time monitoring of large-scale and structured dynamical systems. In the first part, balancing-based methods for system-theoretic model reduction of linear time-invariant systems are considered. We …
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PANDAX-II DARK MATTER DETECTOR AND ITS FIRST RESULTS
… I will focus on the PandaX-II experiment, data analysis and its constraints on theoretical models. After a distillation campaign for krypton removal in 2017, the PandaX-II experiment achieved a background level of 0.8×10−3 event/kg/day/keV which was the lowest among similar detectors at the …
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Data-driven adaptive learning systems
… another key component of such systems. It is the algorithm that designs the learning paths, or in other words, selects learning materials for learners based on the information such as the learners' current progresses and skills, learning material contents. In this thesis, we discuss and address …
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Data-driven modeling and transportation data analytics
Data has become increasingly important in transportation research. Unfortunately, existing traffic models, though developed and practiced for decades, are not data driven and therefore inherently incapable of analyzing modern traffic data from multiple sources with different time resolution and …
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In What Ways Do Data-Driven AI Algorithms Impact Complex Real-World Systems and Decision-Making? [In Che Modo Gli Algoritmi di IA Basati sui Dati Impattano i Sistemi Complessi del Mondo Reale e il Processo Decisionale ?]
… artificiale (IA) progettati per elaborare grandi dataset in vari domini applicativi. I dati giocano un ruolo critico in questo contesto, poiché contengono informazioni preziose che guidano il processo decisionale. I dati grezzi vengono utilizzati dagli algoritmi di IA per estrarre conoscenza, …