Making Meta-learning Generalised . This project aims to develop novel machine learning techniques, termed generalised meta-learning, to make machines better utilise past experience to solve new tasks with few data. It expects to reduce the undesirable dependence of current machine learning on labelled data and significantly expand its application scope. Expected outcomes of the project consist of new theoretical results on meta-learning and a set of innovative algorithms that can support the bui ....Making Meta-learning Generalised . This project aims to develop novel machine learning techniques, termed generalised meta-learning, to make machines better utilise past experience to solve new tasks with few data. It expects to reduce the undesirable dependence of current machine learning on labelled data and significantly expand its application scope. Expected outcomes of the project consist of new theoretical results on meta-learning and a set of innovative algorithms that can support the building of next generation of computer vision systems to work in open and dynamic environments. This should be able to produce solid benefits to the science, society, and economy of Australian via the application of these advanced intelligent systems.Read moreRead less
Exploring Scientific Information with Advanced New Search Tools. The rapidly growth of scientific literature in many fields makes finding information a challenge. For example, biologists produce over 1 million articles each year. Existing search tools have only limited success satisfying the demands of scientists' queries. This project will deliver intelligent e-research assistants capable of answering scientists' questions directly rather than returning a list of documents. This will allow scie ....Exploring Scientific Information with Advanced New Search Tools. The rapidly growth of scientific literature in many fields makes finding information a challenge. For example, biologists produce over 1 million articles each year. Existing search tools have only limited success satisfying the demands of scientists' queries. This project will deliver intelligent e-research assistants capable of answering scientists' questions directly rather than returning a list of documents. This will allow scientists to more efficiently exploit the literature enabling them to be more innovative and productive. This technology is applicable where ever finding facts in large volumes of text is critical, e.g. analysing surveillance material. Advanced search tools will have considerable academic and industrial impact.Read moreRead less
Parsing the web: Exploiting redundancy to understand language. This project will automatically learn the grammatical structure of language by exploiting redundancy of facts, like 'Mozart was born in 1756', from a trillion words of web text. These facts will be used to understand more complex sentences. This will enable smart information use of text with grammatical information for large-scale information access for the first time. This project will strengthen Australia's world-class expertise, ....Parsing the web: Exploiting redundancy to understand language. This project will automatically learn the grammatical structure of language by exploiting redundancy of facts, like 'Mozart was born in 1756', from a trillion words of web text. These facts will be used to understand more complex sentences. This will enable smart information use of text with grammatical information for large-scale information access for the first time. This project will strengthen Australia's world-class expertise, providing opportunities for future researchers in this area. Our expanded C&C tools and trillion word corpus will be used by academics, companies and governments, in Australia and internationally, aiding applications including financial surveillance and fraud detection.
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Network Intrusion Detection via Machine Learning. Computer security is an increasingly important, yet complex task. It
takes significant skills to configure systems properly such that they
are safe from malicious attacks.
The proposed project aims at designing automatic systems which are
able to adapt to an existing network configuration and which detect
novel and unusual events. For this purpose we will use modern machine
learning techniques, mainly based on kernels. In particular, rec ....Network Intrusion Detection via Machine Learning. Computer security is an increasingly important, yet complex task. It
takes significant skills to configure systems properly such that they
are safe from malicious attacks.
The proposed project aims at designing automatic systems which are
able to adapt to an existing network configuration and which detect
novel and unusual events. For this purpose we will use modern machine
learning techniques, mainly based on kernels. In particular, recently
developed algorithms to estimate the support of a distribution and
detect rare events will be employed in this context.
The project is in cooperation with Dr. Ralf Herbrich (Microsoft
Research, Cambridge).
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Ask the Net: Intelligent Natural Language Learning. Natural Language Processing (NLP) has progressed rapidly using corpus-based machine learning techniques. However, corpus development costs cause a ?data bottleneck? which prevents systems from reaching human competence. This project overcomes the difficulties of creating huge corpora by employing the innate language ability of untrained contributors. We will show how to automatically select and present examples, containing informative lingui ....Ask the Net: Intelligent Natural Language Learning. Natural Language Processing (NLP) has progressed rapidly using corpus-based machine learning techniques. However, corpus development costs cause a ?data bottleneck? which prevents systems from reaching human competence. This project overcomes the difficulties of creating huge corpora by employing the innate language ability of untrained contributors. We will show how to automatically select and present examples, containing informative linguistic structures, which are most beneficial for training NLP systems. These examples will be analysed by many contributors whose responses will be automatically collated into corpora. Huge corpora are vital to emerging language technologies for managing textual information in the global economy.
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Computer Vision Optimization Problems Using Machine Learning. Computer Vision concerns itself with understanding the world through the analysis of images obtained by a video or still camera. An important application is tracking of people in video and modelling their movements. This has evident applications in security, sport and entertainment. By enabling the computer to capture the motion of a subject in a video, we may detect suspicious activity in security, analyze the motion (golf-swing, ....Computer Vision Optimization Problems Using Machine Learning. Computer Vision concerns itself with understanding the world through the analysis of images obtained by a video or still camera. An important application is tracking of people in video and modelling their movements. This has evident applications in security, sport and entertainment. By enabling the computer to capture the motion of a subject in a video, we may detect suspicious activity in security, analyze the motion (golf-swing, diving style) of a sports-person, or capture the motion of an actor for animation or game applications. Development of a reliable technology requires new optimization techniques, which will place Australia at the forefront of the application of such research, commercially and for the public benefit.Read moreRead less
Lexical retrieval and reading comprehension: Binding perceptual, lexical and conceptual information in on-line reading. Reading is a complex process that involves integrating sensory information extracted from text with stored memories about word meanings, syntactic structures and general knowledge. Most reading research has focused on the processing of isolated words, but normal reading requires integration processes that are not necessary to recognise single words. This research uses tasks req ....Lexical retrieval and reading comprehension: Binding perceptual, lexical and conceptual information in on-line reading. Reading is a complex process that involves integrating sensory information extracted from text with stored memories about word meanings, syntactic structures and general knowledge. Most reading research has focused on the processing of isolated words, but normal reading requires integration processes that are not necessary to recognise single words. This research uses tasks requiring sentence comprehension and measures of eye movements during reading to investigate how readers retrieve and combine information while reading to comprehend text. It will contribute to developing more comprehensive theories of normal reading that can inform methods of teaching reading and contribute to refinement of text recognition systems.Read moreRead less
Personalised Online Learning Analytics by Exploring Multilayer Graph Data . Learning analytics is becoming a significant factor in reducing the drop-out rate of students in online learning. The aim of this project is to develop a reliable, robust, real-time analysis system that automatically reveals multilayered relationships, evaluates students' learning performance, and generates a personal study plan through discovery. This project includes the design of novel algorithms for multilayer graph ....Personalised Online Learning Analytics by Exploring Multilayer Graph Data . Learning analytics is becoming a significant factor in reducing the drop-out rate of students in online learning. The aim of this project is to develop a reliable, robust, real-time analysis system that automatically reveals multilayered relationships, evaluates students' learning performance, and generates a personal study plan through discovery. This project includes the design of novel algorithms for multilayer graph processing, pattern recognition in learning activities, learning performance assessment, and personalised study plan recommendations. The success of this project will significantly enhance the success of online education both in Australia and worldwide and; hence, will save time, money and resources for end users.Read moreRead less
Small Scalable Natural Language Models using Explicit Memory. Deep neural networks have had spectacular success in natural language processing, seeing wide-spread deployment as part of automatic assistant devices in homes and cars, and across many valuable industries including finance, medicine and law. Fueling this success is the use of ever larger models, with exponentially increasing training resources, accompanying hardware and energy demands. This project aims to develop more compact models ....Small Scalable Natural Language Models using Explicit Memory. Deep neural networks have had spectacular success in natural language processing, seeing wide-spread deployment as part of automatic assistant devices in homes and cars, and across many valuable industries including finance, medicine and law. Fueling this success is the use of ever larger models, with exponentially increasing training resources, accompanying hardware and energy demands. This project aims to develop more compact models, based on the incorporation of an explicit searchable memory, which will dramatically reduce model size, hardware requirements and energy usage. This will make modern natural language processing more accessible, while also providing greater flexibility, allowing for more adaptable and portable technologies.Read moreRead less
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