A Novel Approach to Semi-Supervised Statistical Machine Learning. Recent successes in the construction of classifiers for making diagnoses and predictions are due in part to their using much data labelled with respect to their class of origin. But typically there are little labelled data but plentiful unlabelled data. The goal of semi-supervised learning (SSL) is to leverage large amounts of unlabelled data to improve the performance using only small labelled datasets and so SSL is of paramount ....A Novel Approach to Semi-Supervised Statistical Machine Learning. Recent successes in the construction of classifiers for making diagnoses and predictions are due in part to their using much data labelled with respect to their class of origin. But typically there are little labelled data but plentiful unlabelled data. The goal of semi-supervised learning (SSL) is to leverage large amounts of unlabelled data to improve the performance using only small labelled datasets and so SSL is of paramount importance to applications where it is expensive or impractical to obtain much labelled data. The project is to develop a novel SSL approach that adopts a missingness mechanism for the missing labels to build a classifier that not only improves accuracy but it can be greater than if the missing labels were known.
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Advanced Mixture Models for the Analysis of Modern-Day Data. Extracting key information from huge data sets is critical to the scientific successes of the future. This project will develop novel mixture models that can be used directly to analyse complex and high-dimensional data sets that may consist of thousands of variables observed on only a limited number of entities. In order to handle the challenging problems arising in the latter situation. This project develops mixtures of factor models ....Advanced Mixture Models for the Analysis of Modern-Day Data. Extracting key information from huge data sets is critical to the scientific successes of the future. This project will develop novel mixture models that can be used directly to analyse complex and high-dimensional data sets that may consist of thousands of variables observed on only a limited number of entities. In order to handle the challenging problems arising in the latter situation. This project develops mixtures of factor models with options for skew distributions that can be used to effectively analyse such data. Key applications include the domains of bioinformatics, biostatistics, business, data mining, economics, finance, image analysis, marketing, and personalised medicine, among many others.Read moreRead less
Joint clustering and matching of multivariate samples across objects. The project will provide a novel and very effective approach to the clustering of multivariate samples on objects, say patients, that automatically matches the sample clusters across the objects. A key application is the matching of biologically relevant cell subtypes across patients for use in the study and the clinical diagnosis and prognosis of cancer.
Expanding the role of mixture models in statistical analyses of big data. This project aims to develop theoretical procedures to scale inference and learning algorithms to analyse big data sets. It will develop analytic tools and algorithms to analyse big data sets which classical methods of inference cannot analyse directly due to the data’s complexity or size. This will accelerate the progress of scientific discovery and innovation, leading, for example, to new fields of inquiry; to an increas ....Expanding the role of mixture models in statistical analyses of big data. This project aims to develop theoretical procedures to scale inference and learning algorithms to analyse big data sets. It will develop analytic tools and algorithms to analyse big data sets which classical methods of inference cannot analyse directly due to the data’s complexity or size. This will accelerate the progress of scientific discovery and innovation, leading, for example, to new fields of inquiry; to an increase in understanding from studies on human and social processes and interactions; and to the promotion of economic growth and improved health and quality of life. Such applications should lead to breakthrough discoveries and innovation in science, engineering, medicine, commerce, education and national security.Read moreRead less
A new approach to fast matrix factorization for the statistical analysis of high-dimensional data. Some form of dimension reduction is essential in order to extract meaningful information from huge data sets. For this purpose we provide a novel and very fast approach to the factorization of the data matrix. It has wide applicability for improving the quality and validity of research in science and medicine and in most industries in Australia.
Large-Scale Statistical Inference: Multiple Testing. Multiple testing procedures are among the most important statistical tools for the analysis of modern data. This project aims to develop new methods for providing more powerful simultaneous tests while controlling the proportion of false positive conclusions. They are proposed to be derived by the novel pooling of information in individual attribute based contrasts to produce a Weighted Individual attribute-Specific Contrast (WISC) based stati ....Large-Scale Statistical Inference: Multiple Testing. Multiple testing procedures are among the most important statistical tools for the analysis of modern data. This project aims to develop new methods for providing more powerful simultaneous tests while controlling the proportion of false positive conclusions. They are proposed to be derived by the novel pooling of information in individual attribute based contrasts to produce a Weighted Individual attribute-Specific Contrast (WISC) based statistic. They will also exploit contextual information. They are expected to be of direct application to the problem of testing for no differences between two or more classes, as in the detection of differential expression in bioinformatics. Other key applications are expected to include biomedicine, economics, finance, genetics, and neuroscience.Read moreRead less
Relaxed correctness criteria for modern multi-core architectures. This project seeks to lay groundwork for fully exploiting the potential of multicore computers. Multicore computers have become ubiquitous over the last decade, now being standard in everything from laptops to mobile phones. Their benefits are clear – better performance leading to more sophisticated applications. Key to ensuring those benefits are complex, and often subtle, algorithms that exploit the parallelism that multicore co ....Relaxed correctness criteria for modern multi-core architectures. This project seeks to lay groundwork for fully exploiting the potential of multicore computers. Multicore computers have become ubiquitous over the last decade, now being standard in everything from laptops to mobile phones. Their benefits are clear – better performance leading to more sophisticated applications. Key to ensuring those benefits are complex, and often subtle, algorithms that exploit the parallelism that multicore computers offer. This project aims to lay foundations for extending those benefits to applications where high reliability is a concern. It plans to do so by developing theoretical results about the correctness of algorithms on standard multicore computers, and practical tools and techniques to help programmers of multicore computers to better understand the behaviour of their code.Read moreRead less
The Ethics of Voluntary Assisted Dying: Promoting Constructive Debate. This project aims to analyze core concepts that play key roles in emerging debates about the ethics of Voluntary Assisted Dying (VAD) in Australia. The project expects to make constructive contributions to these debates, promoting respectful dialogue and reducing polarization. Expected outcomes include a new model for managing VAD in Australia which is ethically appropriate and consistent with community values. This model wil ....The Ethics of Voluntary Assisted Dying: Promoting Constructive Debate. This project aims to analyze core concepts that play key roles in emerging debates about the ethics of Voluntary Assisted Dying (VAD) in Australia. The project expects to make constructive contributions to these debates, promoting respectful dialogue and reducing polarization. Expected outcomes include a new model for managing VAD in Australia which is ethically appropriate and consistent with community values. This model will also benefit other countries where the ethics of VAD is under consideration. The project will promote the dignity and autonomy of all and ensure that issues about the conscientious refusal of healthcare professionals to participate in the provision of VAD are handled in an ethically appropriate and effective manner.Read moreRead less
SenShaMart: A Trusted Internet of Things Marketplace for Sensor Sharing. This project aims to devise a novel Internet of Things (IoT) sensor sharing marketplace that permits IoT applications to discover, integrate, and pay for any IoT sensor data that is made available by other parties. The project will devise highly-scalable sensor classification, query processing, and transactions solutions and incorporate them in a pair of novel blockchains that work in tandem to securely manage all the infor ....SenShaMart: A Trusted Internet of Things Marketplace for Sensor Sharing. This project aims to devise a novel Internet of Things (IoT) sensor sharing marketplace that permits IoT applications to discover, integrate, and pay for any IoT sensor data that is made available by other parties. The project will devise highly-scalable sensor classification, query processing, and transactions solutions and incorporate them in a pair of novel blockchains that work in tandem to securely manage all the information and contracts needed by IoT applications to discover, integrate, pay, and use sensors provided by another parties. These IoT advancements will provide significant economic, environmental, and social benefits via making low-cost and immediate sensing available across the world.Read moreRead less
Income insecurity in Australia: who is feeling the pinch and why? This project aims to measure and investigate the drivers of income insecurity in Australia. It will provide an evaluation of whether income growth is sufficient to compensate for any welfare loss due to higher income risk and the effectiveness of government taxes and transfers in alleviating income risks for different population sub-groups.