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Full-Text Articles in Physical Sciences and Mathematics
Learning Mortality Risk For Covid-19 Using Machine Learning And Statistical Methods, Shaoshi Zhang
Learning Mortality Risk For Covid-19 Using Machine Learning And Statistical Methods, Shaoshi Zhang
Electronic Thesis and Dissertation Repository
This research investigates the mortality risk of COVID-19 patients across different variant waves, using the data from Centers for Disease Control and Prevention (CDC) websites. By analyzing the available data, including patient medical records, vaccination rates, and hospital capacities, we aim to discern patterns and factors associated with COVID-19-related deaths.
To explore features linked to COVID-19 mortality, we employ different techniques such as Filter, Wrapper, and Embedded methods for feature selection. Furthermore, we apply various machine learning methods, including support vector machines, decision trees, random forests, logistic regression, K-nearest neighbours, na¨ıve Bayes methods, and artificial neural networks, to uncover underlying …
Algebraic Neural Architecture Representation, Evolutionary Neural Architecture Search, And Novelty Search In Deep Reinforcement Learning, Ethan C. Jackson
Algebraic Neural Architecture Representation, Evolutionary Neural Architecture Search, And Novelty Search In Deep Reinforcement Learning, Ethan C. Jackson
Electronic Thesis and Dissertation Repository
Evolutionary algorithms have recently re-emerged as powerful tools for machine learning and artificial intelligence, especially when combined with advances in deep learning developed over the last decade. In contrast to the use of fixed architectures and rigid learning algorithms, we leveraged the open-endedness of evolutionary algorithms to make both theoretical and methodological contributions to deep reinforcement learning. This thesis explores and develops two major areas at the intersection of evolutionary algorithms and deep reinforcement learning: generative network architectures and behaviour-based optimization. Over three distinct contributions, both theoretical and experimental methods were applied to deliver a novel mathematical framework and experimental …