Stochastic majorization--minimization algorithms for data science. The changing nature of acquisition and storage data has made the process of drawing inference infeasible with traditional statistical and machine learning methods. Modern data are often acquired in real time, in an incremental nature, and are often available in too large a volume to process on conventional machinery. The project proposes to study the family of stochastic majorisation-minimisation algorithms for computation of inf ....Stochastic majorization--minimization algorithms for data science. The changing nature of acquisition and storage data has made the process of drawing inference infeasible with traditional statistical and machine learning methods. Modern data are often acquired in real time, in an incremental nature, and are often available in too large a volume to process on conventional machinery. The project proposes to study the family of stochastic majorisation-minimisation algorithms for computation of inferential quantities in an incremental manner. The proposed stochastic algorithms encompass and extend upon a wide variety of current algorithmic frameworks for fitting statistical and machine learning models, and can be used to produce feasible and practical algorithms for complex models, both current and future.
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Statistical methods for quantifying variation in spatiotemporal areal data. This project aims to develop new statistical methods for extracting insights into spatial and temporal variation in areal data. These tools will extend the Australian Cancer Atlas which provides small area estimates for 20 cancers across Australia. The project is significant because it will allow government and other organisations to reap dividends from investment in collecting spatial information and it will enable mode ....Statistical methods for quantifying variation in spatiotemporal areal data. This project aims to develop new statistical methods for extracting insights into spatial and temporal variation in areal data. These tools will extend the Australian Cancer Atlas which provides small area estimates for 20 cancers across Australia. The project is significant because it will allow government and other organisations to reap dividends from investment in collecting spatial information and it will enable modelled small-area estimates to be released without compromising confidentiality. The expected outcomes include new statistical knowledge and new insights into cancer. The results will benefit the many disciplines, managers and policy makers that make decisions based on geographic data mapped over space and time. Read moreRead less
Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predi ....Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predictive sensory data analytics. This should provide significant benefits, such as substantially reduced operating and service costs and improved accuracy for real-time monitoring in the fields where cheap-to-implement and easy-to-service monitoring systems over large geographical areas are imperative.Read moreRead less
Privacy-preserving data processing on the cloud. This project aims to address the current lack of privacy of user data processed by common cloud computing web servers, including email, business data, and confidential files. This project aims to develop new techniques in cryptography. The anticipated outcome is a suite of practical tools enabling common cloud computing processing operations such as search, statistical analysis, and multi-user access control, to be performed efficiently while pres ....Privacy-preserving data processing on the cloud. This project aims to address the current lack of privacy of user data processed by common cloud computing web servers, including email, business data, and confidential files. This project aims to develop new techniques in cryptography. The anticipated outcome is a suite of practical tools enabling common cloud computing processing operations such as search, statistical analysis, and multi-user access control, to be performed efficiently while preserving the data privacy. These tools should provide significant benefits to the privacy of cloud users, as well as financial and reputation benefits to the IT industry, by significantly reducing the likelihood of massive user data privacy breaches in the event of a cyber-hacking attack on the cloud server.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE170100033
Funder
Australian Research Council
Funding Amount
$900,000.00
Summary
Australian Acoustic Observatory: A network to monitor biodiversity. This project aims to create a terrestrial acoustic sensor network comprising 450 listening stations across Australia. Acoustic sensing transforms environmental science by recording vocal species 24/7, providing spatial and temporal data for ecosystem monitoring and research. Australia has leading research expertise in this emerging field, which is relevant to its fragile and mega-diverse environment. This project is expected to ....Australian Acoustic Observatory: A network to monitor biodiversity. This project aims to create a terrestrial acoustic sensor network comprising 450 listening stations across Australia. Acoustic sensing transforms environmental science by recording vocal species 24/7, providing spatial and temporal data for ecosystem monitoring and research. Australia has leading research expertise in this emerging field, which is relevant to its fragile and mega-diverse environment. This project is expected to enable and develop continental scale environmental monitoring, and the data generated will be made freely available to all online, enabling new science in understanding ecosystems, long-term environmental change, data visualisation and acoustic science.Read moreRead less
Predicting the value and use of urban land. This project aims to develop a comprehensive, robust and user-friendly set of modelling tools to predict land values more accurately. Accurate predictions of land values reduce state government revenue risks and improve resource management. The expected outcome of this project is the development of modelling tools which, can be used to study land use allocation, infrastructure delivery and government taxation revenue. This should provide significant be ....Predicting the value and use of urban land. This project aims to develop a comprehensive, robust and user-friendly set of modelling tools to predict land values more accurately. Accurate predictions of land values reduce state government revenue risks and improve resource management. The expected outcome of this project is the development of modelling tools which, can be used to study land use allocation, infrastructure delivery and government taxation revenue. This should provide significant benefits such as the development of new econometric theory, advanced computational methods and evidence-based guidelines for policymakers.Read moreRead less
Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less
Measuring the Commercial Real Estate Sector in Australia. This project aims to address a significant gap in our understanding of the Australian commercial real estate sector. It will use detailed data to develop sophisticated models of the prices of commercial buildings. Expected outcomes include a suite of commercial real estate price indexes for Australia, by region and property type, and a comprehensive and transparent examination of the methods used to construct them. This will shed light on ....Measuring the Commercial Real Estate Sector in Australia. This project aims to address a significant gap in our understanding of the Australian commercial real estate sector. It will use detailed data to develop sophisticated models of the prices of commercial buildings. Expected outcomes include a suite of commercial real estate price indexes for Australia, by region and property type, and a comprehensive and transparent examination of the methods used to construct them. This will shed light on a hitherto poorly measured sector and provide significant benefits by better informing market participants, guiding statistical agencies in developing such measures and better-enabling policymakers, banks, superfunds and macroprudential authorities to understand the risk profile of the sector.Read moreRead less
Enabling Automatic Graph Learning Pipelines with Limited Human Knowledge. This project aims to develop an automatic graph learning system for complex graph data analysis. Machine learning for graph data commonly requires significant human knowledge from both domain professionals as well as algorithm experts, rendering existing systems ineffective and unexplainable. This project expects to design novel graph learning techniques which automatically infer graph relations, learn graph models, adapts ....Enabling Automatic Graph Learning Pipelines with Limited Human Knowledge. This project aims to develop an automatic graph learning system for complex graph data analysis. Machine learning for graph data commonly requires significant human knowledge from both domain professionals as well as algorithm experts, rendering existing systems ineffective and unexplainable. This project expects to design novel graph learning techniques which automatically infer graph relations, learn graph models, adapts existing knowledge to new domains, and provide explanations to the graph learning system. The research results should provide benefit to governments and businesses in many critical applications, such as bioassay activity prediction, credit assessment, and drug discovery and vaccine development in response to the pandemic.Read moreRead less