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Australian State/Territory : VIC
Research Topic : Machine tools
Status : Closed
Australian State/Territory : SA
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  • Funded Activity

    Discovery Projects - Grant ID: DP180103600

    Funder
    Australian Research Council
    Funding Amount
    $290,011.00
    Summary
    Where do inductive biases come from? A Bayesian investigation. This project aims to investigate the origin of our thinking and learning biases using state-of-the-art mathematical models and sophisticated experimental designs. Expected outcomes include bridging the gap between human and machine learning by pairing mathematical modelling with experimental work, forming a necessary step toward the development of machine systems that can reason like people do. This will provide significant benefits .... Where do inductive biases come from? A Bayesian investigation. This project aims to investigate the origin of our thinking and learning biases using state-of-the-art mathematical models and sophisticated experimental designs. Expected outcomes include bridging the gap between human and machine learning by pairing mathematical modelling with experimental work, forming a necessary step toward the development of machine systems that can reason like people do. This will provide significant benefits such as understanding how people operate so effectively in real environments, when even the most powerful computers struggle to handle the complexities of everyday learning problems.
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    Funded Activity

    Discovery Projects - Grant ID: DP150103280

    Funder
    Australian Research Council
    Funding Amount
    $301,300.00
    Summary
    Learning from others: Inductive reasoning based on human-generated data. Most of the data we see every day, from politics to gossip, comes from other people. Making inferences about such data is difficult because the people who provided it may have biases or limitations in their knowledge that we do not know about and must figure out. This project uses a series of experiments tied to normative computational models of social reasoning to explore how people solve this problem. This work has the po .... Learning from others: Inductive reasoning based on human-generated data. Most of the data we see every day, from politics to gossip, comes from other people. Making inferences about such data is difficult because the people who provided it may have biases or limitations in their knowledge that we do not know about and must figure out. This project uses a series of experiments tied to normative computational models of social reasoning to explore how people solve this problem. This work has the potential to make a major impact in understanding how information is understood and shared, especially when it is about topics that people lack firsthand knowledge about, like climate change. The computational models also have applications to the development of expert systems upon which our information economy relies.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE140101749

    Funder
    Australian Research Council
    Funding Amount
    $379,480.00
    Summary
    A computational network model of the mental lexicon. Understanding a word's meaning is a challenge when learning a language and a capacity that is seriously affected in various disorders such as Alzheimer's disease, however little is known about how meaning is organised in the mental lexicon and evolves from childhood into old age. This project aims to build a detailed computational model integrating information available through the senses and structure in the language environment to derive a l .... A computational network model of the mental lexicon. Understanding a word's meaning is a challenge when learning a language and a capacity that is seriously affected in various disorders such as Alzheimer's disease, however little is known about how meaning is organised in the mental lexicon and evolves from childhood into old age. This project aims to build a detailed computational model integrating information available through the senses and structure in the language environment to derive a lexicon that covers most words people know. By distinguishing qualitative different types of meaning relations, this project will allow the prediction of the kind of information and processes required to understand words and an understanding of how this lexicon grows in childhood and declines in old age.
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    Funded Activity

    Research Networks - Grant ID: RN0459895

    Funder
    Australian Research Council
    Funding Amount
    $1,600,000.00
    Summary
    ARC Research Network in Enterprise Information Infrastructure. EII targets consolidated research towards the comprehensive development & establishment of advanced information infrastructures. Its prime purpose is to provide a forum for intellectual exchange by diverse yet complementary research groups, to address the fundamental research problems faced by scientific & business communities when dealing with deployment of information technology to globally distributed, and data intensive environme .... ARC Research Network in Enterprise Information Infrastructure. EII targets consolidated research towards the comprehensive development & establishment of advanced information infrastructures. Its prime purpose is to provide a forum for intellectual exchange by diverse yet complementary research groups, to address the fundamental research problems faced by scientific & business communities when dealing with deployment of information technology to globally distributed, and data intensive environments. EII will address 3 tightly coupled research themes: Ability to interoperate across existing heterogenous platforms & applications; Efficient processing of very large data sets; Technology adoption & impact. Generic results will be applicable to e-science and large business information systems installations.
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    Showing 1-4 of 4 Funded Activites

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