Discovery Early Career Researcher Award - Grant ID: DE170101134

Funding Activity

Website
http://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/DE170101134

Funding Status
Closed

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Funded Activity Summary

Feasible algorithms for big inference. This project aims to develop algorithms for computationally-intensive statistical tools to analyse Big Data. Big Data is ubiquitous in science, engineering, industry and finance, but needs special machine learning to conduct correct inferential analysis. Computational bottlenecks make many tried-and-true tools of statistical inference inadequate. This project will develop tools including false discovery rate control, heteroscedastic and robust regression and mixture models, via Big Data-appropriate optimisation and composite-likelihood estimation. It will make open, well-documented, and accessible software available for the scalable and distributable analysis of Big Data. The expected outcome is a suite of scalable algorithms to analyse Big Data.

Funded Activity Details

Start Date: 28-04-2017

End Date: 31-12-2021

Funding Scheme: Discovery Early Career Researcher Award

Funding Amount: $360,000.00

Funder: Australian Research Council

Research Topics

ANZSRC Field of Research (FoR)

Applied Statistics | Statistical Theory | Pattern Recognition and Data Mining | Statistics |

ANZSRC Socio-Economic Objective (SEO)

Expanding Knowledge in the Information and Computing Sciences | Expanding Knowledge in the Mathematical Sciences

Other Keywords

Applied Statistics | Expanding Knowledge in the Information and Computing Sciences | Expanding Knowledge in the Mathematical Sciences | Pattern Recognition and Data Mining | Statistical Theory | Statistics

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