Asymptotic Geometric Analysis and Learning Theory. Learning Theory is used in various real-world applications in diverse research areas, ranging from Biology (e.g. DNA sequencing) to Information Sciences. Therefore, having a deep understanding of fundamental questions in Learning Theory, and in particular, pin-pointing the parameters that make a learning problem hard would have a significant practical impact. This projects aims to achieve this goal, and in addition, we expect it would have a hig ....Asymptotic Geometric Analysis and Learning Theory. Learning Theory is used in various real-world applications in diverse research areas, ranging from Biology (e.g. DNA sequencing) to Information Sciences. Therefore, having a deep understanding of fundamental questions in Learning Theory, and in particular, pin-pointing the parameters that make a learning problem hard would have a significant practical impact. This projects aims to achieve this goal, and in addition, we expect it would have a high theoretical value, as the questions we shall address are of independent interest to pure mathematicians.Read moreRead less
Asymptotic Geometric Analysis and Learning Theory. Learning Theory is used in various real-world applications in diverse research areas, ranging from Biology (e.g. DNA sequencing) to Information Sciences. Therefore, having a deep understanding of fundamental questions in Learning Theory, and in particular, pin-pointing the parameters that make a learning problem hard would have a significant practical impact. This projects aims to achieve this goal, and in addition, we expect it would have a hig ....Asymptotic Geometric Analysis and Learning Theory. Learning Theory is used in various real-world applications in diverse research areas, ranging from Biology (e.g. DNA sequencing) to Information Sciences. Therefore, having a deep understanding of fundamental questions in Learning Theory, and in particular, pin-pointing the parameters that make a learning problem hard would have a significant practical impact. This projects aims to achieve this goal, and in addition, we expect it would have a high theoretical value, as the questions we shall address are of independent interest to pure mathematicians.
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Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an ....Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an open-source tool that can capture precision correlations between deep code features and diverse vulnerabilities to pinpoint emerging vulnerabilities without the need for bug specifications. Significant benefits include greatly improved quality, reliability and security for modern software systems.Read moreRead less
Suction pipette measurements of mammalian rod photoreceptor recovery following intense bleaching exposures. The aim of this project is to discover the events and processes that prevent retinal photoreceptors from recovering instantaneously following the cessation of exposure to extremely bright illumination. Recordings will be made from single rod photoreceptors cells isolated from the mammalian retina. The work will uncover the relative roles of the 'photoproducts' created when rhodopsin abso ....Suction pipette measurements of mammalian rod photoreceptor recovery following intense bleaching exposures. The aim of this project is to discover the events and processes that prevent retinal photoreceptors from recovering instantaneously following the cessation of exposure to extremely bright illumination. Recordings will be made from single rod photoreceptors cells isolated from the mammalian retina. The work will uncover the relative roles of the 'photoproducts' created when rhodopsin absorbs light: e.g. intermediates such as metarhodopsin and opsin. The molecular knowledge obtained will help us to understand why it is that the visual system recovers so slowly after the eye has experienced very intense light.Read moreRead less
Voices of Regional Australia: The linguistic patterning of local attachment. This project aims to investigate language and social dynamics among regional Australians, who, despite representing one third of the population, have been often neglected in the research to date. The project expects to generate new knowledge around regional attachment and the impact that has on speech patterns, adapting for the first time recently developed international metrics to the Australian context. Expected outco ....Voices of Regional Australia: The linguistic patterning of local attachment. This project aims to investigate language and social dynamics among regional Australians, who, despite representing one third of the population, have been often neglected in the research to date. The project expects to generate new knowledge around regional attachment and the impact that has on speech patterns, adapting for the first time recently developed international metrics to the Australian context. Expected outcomes include a better understanding of models of language change across urban and rural areas, and a novel dataset recording the stories of regional Australians, and in particular, their experiences facing bushfire. This should provide significant benefits as a record of life, language and community in regional Australia.Read moreRead less
Geometric parameters in Learning Theory. We aim to investigate the behaviour of geometric parameters which appear naturally in Statistical Learning Theory. Those parameters are used to control the sample complexity, which is the size of a random sample needed to produce an accurate prediction. They are also of independent interest in the local theory of Banach spaces. We shall use geometric methods originating in the local theory of Banach spaces to investigate the parameters and the way they in ....Geometric parameters in Learning Theory. We aim to investigate the behaviour of geometric parameters which appear naturally in Statistical Learning Theory. Those parameters are used to control the sample complexity, which is the size of a random sample needed to produce an accurate prediction. They are also of independent interest in the local theory of Banach spaces. We shall use geometric methods originating in the local theory of Banach spaces to investigate the parameters and the way they influence sample complexity. All the problems we focus on are not only important from the Machine Learning point of view, but are intriguing in their theoretical implications.Read moreRead less
Language processing in children with high functioning autism: Evidence from eye tracking. The language abilities in people with autism predict their response to intervention and their cognitive outcome. Young children with autism with poor language abilities are severely disadvantaged. Yet we understand little about what impedes their language development and their interpretation of what others say. The research findings will make a significant contribution by enriching our understanding of why ....Language processing in children with high functioning autism: Evidence from eye tracking. The language abilities in people with autism predict their response to intervention and their cognitive outcome. Young children with autism with poor language abilities are severely disadvantaged. Yet we understand little about what impedes their language development and their interpretation of what others say. The research findings will make a significant contribution by enriching our understanding of why and how comprehension may go astray, as well as helping us to identify subgroups within the autism population.Read moreRead less
DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting th ....DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting the attractiveness and evolving the system. The project expects to advance deep learning and yield novel DeepHoney technologies with associated publications and open-source software. This should benefit science, society, and the economy by building the next generation of active cyber defence systems. Read moreRead less
Using data mining methods to remove uncertainties in sensor data streams. This project will develop key techniques for removing uncertainties in sensor data streams and thus improve the monitoring quality of sensor networks. The expected outcomes will benefit Australia by enabling improved, lower-cost monitoring of natural resources and management of stock raising.
Reconceiving Machine Learning. The proposed research will develop a new way to consider problems to which machine learning can be applied. Machine learning is crucial enabler of the digital economy. The research will provide better opportunities for Australian industry to gain a competitive advantage with machine learning technology. The framework developed will enable better opportunities for collaborative research and will build and strengthen international linkages.