Investigations into machine learning applications in link analysis. Link analysis is an emerging tool for the detection of patterns in structured data. The detection of pattern in such data can lead to the detection of fraud occurrence, security breaches in computer systems, and patterns of social interactions with a community. It is also popularly applied to applications such as Web search engine designs and marketing analysis. This project aims to advance the area of link analysis by allowing ....Investigations into machine learning applications in link analysis. Link analysis is an emerging tool for the detection of patterns in structured data. The detection of pattern in such data can lead to the detection of fraud occurrence, security breaches in computer systems, and patterns of social interactions with a community. It is also popularly applied to applications such as Web search engine designs and marketing analysis. This project aims to advance the area of link analysis by allowing the incorporation of contextual information which accounts for relationships among actors properly. Advances in link detection will allow improvements in security and Web services on which a wide field of national bodies rely. This project can help to place Australia at the forefront of this research area.Read moreRead less
Asynchronous Continuous Time Conditioning. Methodology for reasoning about Asynchronous Temporal Conditional Events (ATCE) obtains, complete with logical calculus for causal relations, reasoning about continuous time belief change, and markov chain algorithms calculating joint distributions of ATCE's.
Current techniques, including bayesian nets, are oblivious to temporal aspects; within our model they can be enhanced to recognize dynamic time changes. Ours is the first such unified model and ....Asynchronous Continuous Time Conditioning. Methodology for reasoning about Asynchronous Temporal Conditional Events (ATCE) obtains, complete with logical calculus for causal relations, reasoning about continuous time belief change, and markov chain algorithms calculating joint distributions of ATCE's.
Current techniques, including bayesian nets, are oblivious to temporal aspects; within our model they can be enhanced to recognize dynamic time changes. Ours is the first such unified model and first to link conditional objects with continuous time constraints.
Need for structures we propose arises in diagnostic reasoning, bayesian learning, temporal databases, and time-dependent data mining. Several commercial products (like Microsoft Office Assistant)could apply them forthwith.Read moreRead less
Generalised quantum models of complexity with application to cognitive systems. Non-separable systems surround us. Our transportation, taxation, schooling, environmental and social policies are all interrelated, and it is increasingly recognised that we cannot consider them in isolation. Such systems are generally deemed complex, and it is often impossible to separate them from one another. Despite this, many of our most advanced modelling techniques are grounded in principles of separability a ....Generalised quantum models of complexity with application to cognitive systems. Non-separable systems surround us. Our transportation, taxation, schooling, environmental and social policies are all interrelated, and it is increasingly recognised that we cannot consider them in isolation. Such systems are generally deemed complex, and it is often impossible to separate them from one another. Despite this, many of our most advanced modelling techniques are grounded in principles of separability and non-contextuality. This project will develop a new set of models of non-separable systems and complexity that will in turn lead to new frontier technologies and theories.Read moreRead less
From Universal Induction to Intelligent Systems. The dream of creating artificial devices that (out)reach human intelligence is an old one. What makes this challenge so interesting? A solution would have enormous implications for our society, and there are arguments that the AI problem might be solved within a couple of decades. Specialized intelligent systems are actually already pervasive (finger print, handwriting, speech, and face recognition; spam filtering; search engines; computer chess; ....From Universal Induction to Intelligent Systems. The dream of creating artificial devices that (out)reach human intelligence is an old one. What makes this challenge so interesting? A solution would have enormous implications for our society, and there are arguments that the AI problem might be solved within a couple of decades. Specialized intelligent systems are actually already pervasive (finger print, handwriting, speech, and face recognition; spam filtering; search engines; computer chess; robots). This decade the first presumably complete mathematical theory of AI has been proposed. By working out this theory, this project will significantly contribute to the foundations of inductive inference and AI, and ultimately lead to smarter software and intelligent systems.Read moreRead less
Service-oriented negotiation and coordination in multi-agent systems. Australia has a strong competitive advantage in the area of agent software. The outcomes of this project will provide an improved platform for services in application areas such as finance, e-commerce, tourism, and multi-platform media. More broadly, the work proposed here will enable the IT industry in Australia, and Melbourne specifically, to adopt and utilise agent-technology in developing the complex software that is inc ....Service-oriented negotiation and coordination in multi-agent systems. Australia has a strong competitive advantage in the area of agent software. The outcomes of this project will provide an improved platform for services in application areas such as finance, e-commerce, tourism, and multi-platform media. More broadly, the work proposed here will enable the IT industry in Australia, and Melbourne specifically, to adopt and utilise agent-technology in developing the complex software that is increasingly required to meet the needs of the software-driven knowledge economy of the 21st century.Read moreRead less
Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering ap ....Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering applications which will both reduced the bandwidth required and make the internet safer for users. Finally, it will enable rapid deployment of sensor networks for monitoring and detection, such as for environmental monitoring and safeguarding Australia's borders.Read moreRead less
Investigating evidence of control system dynamics in visuomotor skill acquisition using multimodal functional magnetic resonance imaging. This project brings together mathematical and engineering methods with cognitive neuroscience in a novel way to better understand the fundamental processes associated with brain imaging, and the acquisition of motor skills. An improved understanding of the function of regions within the motor network will have a direct benefit for the rehabilitation of patient ....Investigating evidence of control system dynamics in visuomotor skill acquisition using multimodal functional magnetic resonance imaging. This project brings together mathematical and engineering methods with cognitive neuroscience in a novel way to better understand the fundamental processes associated with brain imaging, and the acquisition of motor skills. An improved understanding of the function of regions within the motor network will have a direct benefit for the rehabilitation of patients suffering motor deficits from developmental causes, following traumatic brain injuries, and after stroke and other neurodegenerative diseases. The outcomes of the research will also contribute to our understanding of the complexity of brain networks involved in motor skill acquisition.Read moreRead less
High-performance computational data-mining techniques for feature detection in complex time series from large-scale, networked plasma experiments. Terabytes of data are gathered from large experimental facilities as complex time-series. Analysis of these data is daunting, especially when they involve high-dimensional spectral or image arrays. We will develop high-performance computational techniques for dimension reduction, efficient data-mining, and experimental control, using as an initial ta ....High-performance computational data-mining techniques for feature detection in complex time series from large-scale, networked plasma experiments. Terabytes of data are gathered from large experimental facilities as complex time-series. Analysis of these data is daunting, especially when they involve high-dimensional spectral or image arrays. We will develop high-performance computational techniques for dimension reduction, efficient data-mining, and experimental control, using as an initial target the H-1NF plasma fusion MNRF at the ANU and its >100 GB/year data stream. The techniques will immediately provide Australian researchers with unique tools for collaboration in international research to develop fusion as a low-emissions source of electricity, and will be applicable to complex time-series analysis in other areas of science, medicine, and defence.Read moreRead less
The Time-Varying Eigenvalue Problem with Application to Signal Processing and Control. Linear models are ubiquitous in representing physical processes. Decomposing a linear model into its fundamental components is known as the eigenvalue problem. In applications as wide ranging as astronomy, aircraft control systems, Internet search engines and communication systems, it is necessary to perform this decomposition of a pertinent time varying linear model on the fly. This project aims to develop si ....The Time-Varying Eigenvalue Problem with Application to Signal Processing and Control. Linear models are ubiquitous in representing physical processes. Decomposing a linear model into its fundamental components is known as the eigenvalue problem. In applications as wide ranging as astronomy, aircraft control systems, Internet search engines and communication systems, it is necessary to perform this decomposition of a pertinent time varying linear model on the fly. This project aims to develop significantly faster and more accurate algorithms for this time varying eigenvalue problem than currently exist. Very modern techniques will be employed to achieve this aim, and the potential benefits to Australian hi-tech industries are great.
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Spatial Cognition—Expressive Representation Formalisms and Effective Reasoning Mechanisms. The project will contribute significantly to the advancement of knowledge in breakthrough science in qualitative spatial reasoning and smart information use in geographic information systems. Expressive spatial languages are important in organising spatial knowledge, defining spatial query languages and guiding spatial data mining. Effective spatial reasoning mechanisms bring theory closer to applications ....Spatial Cognition—Expressive Representation Formalisms and Effective Reasoning Mechanisms. The project will contribute significantly to the advancement of knowledge in breakthrough science in qualitative spatial reasoning and smart information use in geographic information systems. Expressive spatial languages are important in organising spatial knowledge, defining spatial query languages and guiding spatial data mining. Effective spatial reasoning mechanisms bring theory closer to applications including consistency checking and spatial query pre-processing. The project will help in extracting knowledge from massive spatial databases, meeting the growing needs of naive users for spatial information and establishing Australia as a major player in spatial cognition research and in the development of geo-location services.Read moreRead less