Discovery Early Career Researcher Award - Grant ID: DE230101329

Funding Activity

Website
http://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/DE230101329

Funding Status
Active

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Funded Activity Summary

Trading Privacy, Bandwidth and Accuracy in Algorithmic Machine Learning. This project aims to investigate the trade-offs between privacy, communication costs and accuracy of results when learning from users' sensitive data. The project intends to design faster and more accurate algorithms for a wide range of machine learning tasks by developing a novel and widely-applicable algorithmic framework. Expected outcomes of this project include new theoretical tools to guide the design of data-driven decision systems and rigorously analyse their performance and privacy guarantees. Privacy of individuals' information in data analytics pipelines is a key societal concern. This project should lead to significant benefits by strengthening privacy in these pipelines while also improving accuracy and cost-efficiency.

Funded Activity Details

Start Date: 01-01-2023

End Date: 31-12-2025

Funding Scheme: Discovery Early Career Researcher Award

Funding Amount: $432,355.00

Funder: Australian Research Council

Research Topics

ANZSRC Field of Research (FoR)

Data structures and algorithms | Data and information privacy | Theory of computation |

ANZSRC Socio-Economic Objective (SEO)

Other Keywords

Artificial Intelligence | Cybersecurity | Data and information privacy | Data structures and algorithms | Theory of computation

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