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Federated learning (FL) is an emerging machine learning paradium to enable distributed clients (e.g., mobile devices) to jointly train a machine learning model without pooling their raw data into a
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representations complicate transparency and compliance checks with data protection and privacy legislation (e.g., GDPR) whether performed by humans or computer systems. Second, both privacy-preserving distributed
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Species’ distributions are shifting in response to global climate change and other human pressures. Accurate methods to monitor and predict distribution shifts are urgently needed to manage
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Journal (special issue on Kolmogorov complexity), Vol. 42, No. 4, pp270-283 Wallace, C.S. and D.L. Dowe (2000). MML clustering of multi-state, Poisson, von Mises circular and Gaussian distributions
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annum for outstanding students). Additional financial support is available through research and teaching assistance work. The Opportunity Within the Integrated PhD Program, a PhD opportunity is available
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concentration of economists working in health in the Asia-Pacific region and the largest Health Economics PhD program in Australia, reflecting the reputation of our researchers and the quality of their mentorship
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Masters project Supervisors Login Recently added GEMS 2026: Toward Distribution-Robust Medical Imaging Models in the Wild PhD/RA opportunities on Multimodal We have several PhD and Research Assistant (RA
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supervisors, read about our research strengths and initiate an application, all in one place. Browse Research projects Honours and Masters project Supervisors Login Recently added GEMS 2026: Toward Distribution
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learning approaches to enable multi-site collaboration while preserving patient privacy. This ensures more generalized and reliable reconstruction models that can adapt to diverse data distributions
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. #sustainability Project description For distributed renewable micro-grids to become a mature technology, the economics and the reliability have to be equal to or better than today’s distribution grids. The PhD