3 papers
cs.LG2026
Mitigating Privacy Risk via Forget Set-Free Unlearning
Aviraj Newatia, Michael Cooper, Viet Nguyen +1
Training machine learning models requires the storage of large datasets, which often contain sensitive or private data. Storing data is associated with a number of potential risks…
quant-ph2026
Probabilistic Design of Parametrized Quantum Circuits through Local Gate Modifications
Grier M. Jones, Aviraj Newatia, Alexander Lao +3
Within quantum machine learning, parametrized quantum circuits provide flexible quantum models, but their performance is often highly task-dependent, making manual circuit design c…
cs.CL2025
Red Teaming Large Language Models for Healthcare
Vahid Balazadeh, Michael Cooper, David Pellow +32
We present the design process and findings of the pre-conference workshop at the Machine Learning for Healthcare Conference (2024) entitled Red Teaming Large Language Models for He…