Author

Meng Ding

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#machine learning Preprint Oct 2026

On the Limits of Sparse Linear Model with Shuffled Differential Privacy

By extending the score attack framework to user-level data, a new lower bound of $\Omega$ is established for any user-level $(\epsilon,\delta)$-DP, showing that the proposed algorithm is near-optimal with only a gap of the factor $\log(d/k)$.

Yan Zhang, Jiong Tuo, Meng Ding et al. · 0 citations