To access this element change to forms mode OFF
Grant Award View - GA281772-V1
Advanced Machine Learning with Bilevel Optimization
GA ID:
GA281772-V1
Agency:
Australian Research Council
Approval Date:
19-Jan-2023
Variation Publish Date:
14-Mar-2023
Variation Date:
1-Jun-2023
Category:
Humanities, Arts and Social Sciences (HASS) Research
Grant Term:
1-Jun-2023 to 31-May-2026
Value (AUD):
$480,000.00
(GST inclusive where applicable)
Varies:
GA281772
- Advanced Machine Learning with Bilevel Optimization
One-off/Ad hoc:
No
Aggregate Grant Award:
No
PBS Program Name:
ARC 22/23 Discovery
Grant Program:
Discovery Projects
Grant Activity:
Advanced Machine Learning with Bilevel Optimization
Purpose:
There is an urgent need to develop a new machine learning (ML) paradigm that can overcome data-privacy and model-size constraints in real-world applications. This project aims to develop an advanced paradigm of ML with bilevel optimisation, called bilevel ML. A theoretically-guaranteed fast approximate solver and a new fuzzy bilevel learning framework will be developed to achieve the aim in complex situations; a methodology to transfer knowledge and an approach to fast-adapt bilevel optimization solutions when required computing resources change. The anticipated outcomes should significantly improve the reliability of ML with benefits for safety learning and computing resource optimisation in ML-based data analytics.
GO ID:
GO Title:
Discovery Projects for funding commencing in 2023
Internal Reference ID:
DP23 Round 1
Selection Process:
Targeted or Restricted Competitive
Confidentiality - Contract:
No
Confidentiality - Outputs:
No
Grant Recipient Details
Recipient Name:
University of Technology Sydney
Recipient ABN:
77 257 686 961
Grant Recipient Location
Suburb:
ULTIMO
Town/City:
ULTIMO
Postcode:
2007
State/Territory:
NSW
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
NSW
Postcode:
2007
Country:
AUSTRALIA