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. With the widespread adoption of ML algorithms for data analysis and decision-making, preserving the privacy of individuals' data has become a paramount concern. The project focuses on exploring
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Environment and Science & Quantum SensingFull-timeSchool of Environment and ScienceNathan, QLD Senior Lecturer in ICT and Quantum Algorithms (2 Positions)Full-timeSchool of Information and Communication
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the different actors' beliefs and intentions. We will study the properties of such explanations, present algorithms for automatically computing them as well as extensions to existing frameworks and evaluate
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: Developing algorithms to identify patterns and preferences based on service users’ previous content engagement on the headspace website, enabling the generation of tailored service and resource suggestions
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Optimisation methods, such as mixed integer linear programming, have been very successful at decision-making for more than 50 years. Optimisation algorithms support basically every industry behind
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broad range of topics: from model-predictive building control and community battery integration to wind farm optimisation and multi-decade investment planning, we support clever algorithms and data
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defence algorithms are remain a challenge in the research community. Furthermore, most existing AML algorithms can only apply to Euclidean space. How to extend existing AML algorithms to non-Euclidean and
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This PhD project aims to mitigate the data scarcity of new NLP and Multimodal applications by developing novel active learning algorithms. In this project, the student will leverage large foundation
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Seizure prediction algorithms will be developed using the one-of-a-kind ultra-long-term human intracranial EEG dataset obtained from the Neurovista Corporation clinical trial of their Seizure
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Mixed-Integer Programming (MIP) solvers are very powerful tools to solve combinatorial problems that arise in many industries. Modern MIP solvers usually run a sequence of algorithms to solve