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Masters project Supervisors Login Recently added Hybrid Quantum–Classical Algorithms for Scalable Data Systems and Intelligent Analytics Unsupervised Music Emotion Tagging (Affective Computing) AI of Neural
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The relationship between the information-theoretic Bayesian minimum message length (MML) principle and the notion of Solomonoff-Kolmogorov complexity from algorithmic information theory (Wallace and
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. Wallace (1996). MML estimation of the parameters of the spherical Fisher Distribution. In S. Arikawa and A. K. Sharma (eds.), Proc. 7th International Workshop on Algorithmic Learning Theory (ALT'96
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techniques to design new and efficient algorithms that can provide strong protection during the entire life cycle of ML models used on the devices. Research Task I: Investigate ML algorithms and optimisations
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guarantee that what one believes to be one’s secrets will remain secret. Namely, a DP algorithm cannot ensure that private attributes cannot be inferred from publicly observable attributes if they have strong
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group of experts to predict (probabilistically) whether these occupations will be automated, augmented or unaffected by emerging technologies. Using this data, a classification algorithm is then trained
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This project aims to employ advanced machine learning techniques to analyse text, audio, images, and videos for signs of harmful behaviour. Natural language processing algorithms are utilized
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formative assessment and personalised feedback while ensuring fairness, accountability, and transparency. The research will explore a combination of algorithmic design, human–AI interaction, and empirical
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publicly available datasets; 3) Proposing algorithms aimed at improving the accuracy of human activity detection; 4) Implementing these algorithms, evaluating their performance empirically, and comparing
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applications from any area of genomics, including but not limited to: Applied genomics Comparative genomics Computational genomics Ecological genomics Evolutionary genomics Functional genomics Metagenomics