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 5 of 5 for “"Geometry of data"”.
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Designing Provably Convergent Algorithms from the Geometry of Data
… and industrial applications due to its ease of use and seemingly general-purpose capabilities. However, fundamental research into its theoretical properties has lagged behind. While research into why machine learning works is currently limited, research into how we can make machine learning …
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Towards Learning the Geometry of Data: From Diffusion Models to Riemannian Geometry
… self-supervised learning, and Riemannian geometry, paving the way for learning the intrinsic geometry of data manifolds. In chapter 3, we introduce CAFLOW, a conditional normalising flow that improves image-to-image translation by hierarchically modelling image distributions across scales. …
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Learning strictly orthogonal p-order nonnegative Laplacian embedding via smoothed iterative reweighted method
… in spectral clustering to reveal the intrinsic geometry of data in the high dimensional space. Imposing the orthogonality and the nonnegativity constraints can avoid degenerate and negative solutions, respectively. These two attributes are critical yet challenging to achieve simultaneously. …
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Spectral diffusion map approach for structural health monitoring of wind turbine blades using distributed sensors
… engineering field due to the application of Structural Health Monitoring (SHM) for large-scale structures which results in accurately diagnosing the health of structures and enhancing the reliability and robustness of monitoring systems. The multisensor network greatly enhances the …