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20242026
most citedUniversally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence

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quant-ph2026

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

Liou Tang, James Joshi, Ashish Kundu

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…

cs.LG2026

Characterizing Privacy-Audit Alignment in Behavioral Audit of Machine Unlearning

Liou Tang, James Joshi, Ashish Kundu

The removal of learned data from Machine Learning models through Machine Unlearning (MU) has been widely studied; however, there is no agreed-upon scheme for auditing MU. Existing…