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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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challenging data problem. Weak signals from collisions of compact objects can be dug out of noisy time series because we understand what the signal should look like, and can therefore use simple algorithms
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Project description: Nowadays, data-driven machine learning algorithms are well suited to solve real-world problems that require high-level prediction accuracy. However, it seems as if nothing beats
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and Prof Kath Hulse (Swinburne). This PhD project will analyse the role and mechanisms of social communication, learning and social networks in fostering sustainable and energy efficient household
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be Domestic Student i.e. Australian or New Zealand Citizen or Australian Permanent Resident *** for RAISE programme Project Description Using artificial intelligence software and unique algorithms
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Since the 1990s, researchers have known that commonly-used public-key cryptosystems (such as RSA and Diffie-Hellman systems) could be potentially broken using an efficient algorithm running on a
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feasibility, and to facilitate the rapid translation of study findings into registry practice and health data environments. Project goals: The aim of the project is to develop cutting-edge AI algorithms
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The existing deep learning based time series classification (TSC) algorithms have some success in multivariate time series, their accuracy is not high when we apply them on brain EEG time series (65
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-problems concerning: activity capture (incorporating computer vision and sensor information to map and identify changes in the environment); activity representation (modelling of the activity and environment
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. To email your CV and cover letter or for more information please contact, A/Prof Paige Little , Research Director, QUT Biomechanics and Spine Research Group. About the scholarship The Clayton Adam Florence