Discovery Projects - Grant ID: DP230101671

Funding Activity

Website
http://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/DP230101671

Funding Status
Active

Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the .

Funded Activity Summary

A Novel Approach to Semi-Supervised Statistical Machine Learning. Recent successes in the construction of classifiers for making diagnoses and predictions are due in part to their using much data labelled with respect to their class of origin. But typically there are little labelled data but plentiful unlabelled data. The goal of semi-supervised learning (SSL) is to leverage large amounts of unlabelled data to improve the performance using only small labelled datasets and so SSL is of paramount importance to applications where it is expensive or impractical to obtain much labelled data. The project is to develop a novel SSL approach that adopts a missingness mechanism for the missing labels to build a classifier that not only improves accuracy but it can be greater than if the missing labels were known.

Funded Activity Details

Start Date: 01-03-2023

End Date: 28-02-2026

Funding Scheme: Discovery Projects

Funding Amount: $410,000.00

Funder: Australian Research Council

Research Topics

ANZSRC Field of Research (FoR)

Applied statistics | Statistics | Statistical theory

ANZSRC Socio-Economic Objective (SEO)

Other Keywords

Applied statistics | Expanding Knowledge In the Information and Computing Sciences | Expanding Knowledge In the Mathematical Sciences | Statistical theory | Statistics

Related Links