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 8 of 8 for “"Robust ML"”.
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Human-Machine Alignment for Context Recognition in the Wild
… are acquired from the user directly. To perform robust context prediction in this real-world scenario, the machine must handle the egocentric nature of the context, adapt to the changing world and user, and maintain a bidirectional interaction with the user to ensure the user-machine alignment of …
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Predicting Material Properties with Machine Learned Interatomic Potentials
Machine learning interatomic potentials (ML-IPs) have emerged as a promising approach for bridging the gap between quantum electronic structure calculations (QM) and large scale classical molecular modeling simulations and have shifted the development of these many-body force fields to become …
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Advanced Machine Learning Techniques for Biomarker Discovery and Disease Diagnosis Using Metabolomic Data
… intelligence (AI) and machine learning (ML) can be applied to metabolomics to transform complex datasets into clinically meaningful insights. Specifically, this work seeks to advance precision medicine by enabling the discovery of disease-specific biomarkers, improving diagnostic …
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A Machine Learning Approach for Forecasting with Limited Data and for Distant Time Horizons
… attracted the attention of the machine learning (ML) community to produce accurate forecasting models that address the limitations of classical methods. A large part of ML research focuses on innovative algorithms, but another important area is transitioning ML to industry settings. The objective …
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Robust Machine Learning Against Faults in Micro-Controllers and Stragglers in Distributed Training on the Cloud
… in the past decade. Optimally deploying ML models onto smaller devices and efficiently training more powerful ML models in parallel in different distributed system topologies have drawn interests. This thesis studies the robustness of ML models in the two scenarios when deployed on …
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Predictive Customer Lifetime value modeling: Improving customer engagement and business performance
… base. The outcome of this thesis will be a robust ML solution with remarkable prediction accuracy and practical usability within the company. Furthermore, the insights gained from our research will contribute to a broader understanding of CLV in the subscription-based business context, …
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Efficient, robust and uncertainty aware mobile health
… predictions, and, ultimately, they are less robust in real-world applications. Bayesian deep learning or other non-Bayesian probabilistic techniques can naturally quantify such uncertainty. Still, they do come with quite a few drawbacks, the biggest one being the fact that they tend to be …
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Machine-Learning Assisted Atomic Simulations of Defect Dynamics in Multicomponent Concentrated Alloys
… approach that integrates machine learning (ML) with kinetic Monte Carlo (KMC) simulations to efficiently investigate the controversial phenomenon of "sluggish diffusion" in concentrated alloys. As the first step, the Ni-Fe concentrated alloys are used as model systems. The complexity of …