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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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This PhD project is part of a larger project that aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain
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Global Scholars Program Grant The Global Scholars Program Grant is available to students enrolled in the Bachelor of Global Studies to help support the overseas study requirement of the course
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operators for these notions. Over the past fifty years, such non-classical logics have proved vital in computer science and logic-based artificial intelligence: after all, any intelligent agent must be able
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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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Skip to main content Main Menu - Primary Home Projects Supervisors Expression of Interest Contact Computational drug discovery Primary supervisor Geoff Webb Research area Data Science and Artificial
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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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This project focuses on developing algorithms capable of automatically identifying and categorizing mobile ringtones. This involves leveraging machine learning techniques to analyze audio signals
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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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operators for these notions. Over the past fifty years, such non-classical logics have proved vital in computer science and logic-based artificial intelligence: after all, any intelligent agent must be able