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opportunities for a dynamic, ‘Learning Health System’ – where data can be harnessed to inform real-time and personalised decision-making. Existing linked administrative databases already capture Australian women
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placements and simulated placements. To date, our team of practice educators have worked with occupational therapy students to facilitate their learning and development within aged care facilities
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. I clear example would be teams of nurses training in simulated scenarios. Sensors such as positioning trackers, physiological wristbands, microphones and eye trackers could be used to model complex
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ready copy was submitted in October 2003.] Wallace, C.S. (2005), ``Statistical and Inductive Inference by Minimum Message Length '', Springer (Link to the preface [and p vi , also here ]) Wallace, C.S
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techniques for annotation, active learning (based on either deep learning or Bayesian learning), semi-supervised learning, transfer learning, imitation learning, etc., aiming to ensure the data and models
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at the devices, and even if encryption is used to protect ML models, those models can be extracted during dynamic analysis. To secure on-device ML models, in this project, we aim to employ privacy-enhancing
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, Hawaii, U.S.A. P. J. Tan and D. L. Dowe (2003). MML Inference of Decision Graphs with Multi-Way Joins and Dynamic Attributes , Proc. 16th Australian Joint Conference on Artificial Intelligence (AI'03
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– an essential component of a conversational agent that supports blind people in achieving data literacy. In this project, candidates will use a new generation dynamic tactile display as a modality in
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systems and swarm robotics. The project builds on well established computational and mathematical modelling techniques to achieve its aims. Departure points will be agent-based simulations, optimisation
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2005, ISBN 0-262-07262-9. [Final camera ready copy was submitted in October 2003.] David L. Dowe and Nayyar A. Zaidi (2010), "Database Normalization as a By-product of Minimum Message Length Inference