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Towards Robust Learning Systems via Amortized Optimization and Domain Adaptation (Extension 2022-23)

  • Phung, Dinh (Primary Chief Investigator (PCI))
  • Le, Trung (Chief Investigator (CI))
  • Xiang, Yang (Chief Investigator (CI))
  • Zhang, Jun (Chief Investigator (CI))
  • Erfani, Sarah Monazam (Chief Investigator (CI))
  • Leckie, Christopher Andrew (Chief Investigator (CI))
  • Rubinstein, Ben (Chief Investigator (CI))

Project: Research

Project Details

Project Description

Built up from our previous outcomes, we propose an extension of 18 months during 2022-2023. We propose the following three work packages, continue to address the Trustworthy Machine Learning (TML) topic.
Short titleTowards Robust Learning Systems (Extension 23-24)
AcronymTowards Robust Learning Systems (Extension 23-24)
StatusFinished
Effective start/end date15/04/23 → 15/10/25

Funding

  • Department of Defence (Australia): A$254,997.00

Keywords

  • robust machine learning
  • trustworthy AI