Discovery Early Career Researcher Award - Grant ID: DE180100923

Funding Activity

Website
http://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/DE180100923

Funding Status
Active

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Funded Activity Summary

Efficient second-order optimisation algorithms for learning from big data. This project aims to apply a diverse range of scientific computing techniques to design and implement new, second-order methods that can surpass first-order alternatives in the next generation of optimisation methods for large-scale machine learning (ML). Scalable optimisation methods are now an integral part ML in the presence of “big data”. While the development of efficient first-order methods has grown in the ML community, second-order alternatives have largely been ignored. The project expects to facilitate the development of more effective ML algorithms for extraction of knowledge from large data sets.

Funded Activity Details

Start Date: 04-06-2018

End Date: 31-12-2023

Funding Scheme: Discovery Early Career Researcher Award

Funding Amount: $348,575.00

Funder: Australian Research Council

Research Topics

ANZSRC Field of Research (FoR)

Optimisation | Numerical and Computational Mathematics | Knowledge Representation and Machine Learning

ANZSRC Socio-Economic Objective (SEO)

Expanding Knowledge in the Information and Computing Sciences | Application Software Packages (excl. Computer Games) | Expanding Knowledge in the Mathematical Sciences |

Other Keywords

Application Software Packages (excl. Computer Games) | Expanding Knowledge in the Information and Computing Sciences | Expanding Knowledge in the Mathematical Sciences | Knowledge Representation and Machine Learning | Numerical and Computational Mathematics | Optimisation

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