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at primary care and offer optimal use of scarce health system resources. The model will be trained using skin images (clinical and/or dermoscopic) to identify disease relevant features and accurately diagnosis
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determine optimal operating conditions through iterative testing and experimentation. Through this Project, Tronox aims to demonstrate its commitment to sustainable development, resource efficiency, support
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intelligence techniques (e.g., Deep Learning, Statistics, ML, Optimization) in order to (1) understand the nature of critical software defects like vulnerabilities; (2) predict; (3) highlight vulnerable code; (4
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the Faculty of Science. We will apply Bayesian approaches such as the information-theoretic minimum message length (MML) principle and other approaches to develop a path towards statistically-optimal algorithms
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computational methods for modelling social dilemmas that can account for real-world complexity in agents’ behaviour. We will build on novel computational techniques to produce realistic enough models that can be
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in the learning process to either improve algorithm performance or to complement the information provided by the data. It is a practical guide to optimizing the machine learning process, including
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insect colonies. How do independently acting insects achieve a colony-wide optimal or adequate allocation of workforce? How is the required information communicated in the colony? It will also touch on one