Author

Li-Ou Tang

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#machine learning Preprint Jun 2026

Characterizing Privacy-Audit Alignment in Behavioral Audit of Machine Unlearning

This paper describes how much a generic audit scheme that relies solely on querying the model for behavioral signals inevitably results in privacy leakage related to the retained set by providing a geometric transfer theorem that establishes a lower bound on retained set membership distinguishability based on the audit...

Li-Ou Tang, James B. D. Joshi, Ashish Kundu · 0 citations

#machine learning Preprint Sep 2026

Characterizing Privacy Risks of Quantum Machine Learning with Emergent Quantum-Native Access

Quantum Machine Learning (QML) has shown rapid advances by utilizing quantum computing for machine learning tasks. Meanwhile, the privacy risks accompanying QML is also starting to be studied, which inherit privacy leakage channels from"classical"ML and also quantum-unique risks. Existing work on privacy-preserving QML...

Li-Ou Tang, James B. D. Joshi, Ashish Kundu · 0 citations