Special Research Initiatives - Grant ID: SR0354793
Funder
Australian Research Council
Funding Amount
$10,000.00
Summary
A Neural Network: Understanding Brain Function. This proposal focuses on the mechanisms that regulate brain function, particularly those underpinning the changes in circuitry (plasticity) caused by altered inputs. As such, its core goal is to create an interface between researchers in the neurosciences, computational modelling, robotics and cognitive sciences in order to facilitate optimum collaborative interactions, identify key research questions and promote training opportunities across a mul ....A Neural Network: Understanding Brain Function. This proposal focuses on the mechanisms that regulate brain function, particularly those underpinning the changes in circuitry (plasticity) caused by altered inputs. As such, its core goal is to create an interface between researchers in the neurosciences, computational modelling, robotics and cognitive sciences in order to facilitate optimum collaborative interactions, identify key research questions and promote training opportunities across a multidisciplinary spectrum. This will drive an integrated and accelerated program of discovery and technological development, enhancing Australia's leadership in this crucial field and helping to highlight new biotechnology opportunities and capture social and economic benefits for the nation. Read moreRead less
Towards automated and intelligent processing of web-based information. The successful outcome of this project will enhance Australia's research reputation in an important, practical area of ICT, will contribute to emerging Web standards, will produce frontier technology that will eventually be of benefit to Australian industry, and will train several postgraduate students.
Rule-based reasoning systems for complex and dynamic ontologies. The successful outcome of this project will enhance Australia's research reputation in an important, practical area of ICT, will contribute to emerging Web technologies that will eventually be of benefit to Australian industry, and will train several postgraduate students.
Unsupervised learning of finite mixture models in data mining applications. The extraction of useful information from massively large databases is known as data mining. Its broad but vague goal is to find "interesting structure" in the data, which typically leads to breaking the data into clusters. To this end, we consider the fast, efficient, and automatic learning of finite mixture models in hugh data sets without any prior knowledge of the structure. This probabilistic approach to the discove ....Unsupervised learning of finite mixture models in data mining applications. The extraction of useful information from massively large databases is known as data mining. Its broad but vague goal is to find "interesting structure" in the data, which typically leads to breaking the data into clusters. To this end, we consider the fast, efficient, and automatic learning of finite mixture models in hugh data sets without any prior knowledge of the structure. This probabilistic approach to the discovery and validation of group structure in data mining applications will considerably enhance knowledge management and decision support in science, industry, and government.
Read moreRead less