Discovery Early Career Researcher Award - Grant ID: DE240101089

Funding Activity

Website
http://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/DE240101089

Funding Status
Active

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Funded Activity Summary

Trustworthy Hypothesis Transfer Learning. It is urgent to develop a new hypothesis transfer learning scheme that can overcome potential risks when finetuning unreliable large-scale pre-trained models. This project aims to develop an advanced and reliable scheme of hypothesis transfer learning, called Trustworthy Hypothesis Transfer Learning (TrustHTL). A new theoretically guaranteed heterogeneous hypothesis transfer learning framework will be developed to handle heterogeneous situations; a methodology to disinherit risks of pre-trained models and a new fuzzy relation based distributional discrepancy in heterogeneous transfer learning scenarios. The outcomes should significantly improve the reliability of machine learning with benefits for safety learning in data analytics.

Funded Activity Details

Start Date: 01-01-2024

End Date: 31-12-2026

Funding Scheme: Discovery Early Career Researcher Award

Funding Amount: $436,847.00

Funder: Australian Research Council

Research Topics

ANZSRC Field of Research (FoR)

Data mining and knowledge discovery | Machine learning | Semi- and unsupervised learning | Fuzzy computation |

ANZSRC Socio-Economic Objective (SEO)

Other Keywords

Cybersecurity | Data mining and knowledge discovery | Fuzzy computation | Machine learning | Semi- and unsupervised learning

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