DP-EM: Differentially Private Expectation Maximization

Privacy Without Regret: Differentially Private Inference-Time Alignment

Private Inference-Time Pessimism (PrivITP) is introduced, which combines $\chi^2$-regularized rejection sampling with a two-phase Gaussian mechanism, and achieves ex-post $(\epsilon,\delta)$-DP with a privacy cost independent of the number of responses, cleanly decouples the regularization parameter from the privacy pa...

Statistical Properties of Nonparametric MLE under Laplace Noise

Local differential privacy (LDP) protects individuals in a dataset by perturbing each measurement before release. For real-valued data, a widely used mechanism is additive Laplace noise. We study the problem of estimating the distribution of the latent confidential data from the privatized observations via the nonparam...

Privacy Amplification Without Independence: How Far Negative Dependence Carries the Guarantees of Poisson Subsampling

Poisson subsampling is the default sampler in differentially private optimization because its independence makes privacy amplification tractable. Practical systems, however, are moving toward structured participation: random allocation (balls-in-bins), per-epoch allocation, random check-ins, schemes widely believed to...

On the Computational and Statistical Efficiency of the Empirical Maximum Entropy on the Mean Method

It is shown that the MEM dual problem admits a reformulation as an expected risk minimization problem, thereby placing MEM within the modern framework of stochastic optimization and enabling scalable stochastic gradient algorithms for large-scale inverse problems.

Optimizing DP Gaussian Mean Estimation in R

Bounds on the Posterior-to-Prior Ratios for Inclusion Belief under Bounded Differential Privacy

Differential privacy has become the standard for generating privacy-protected data releases. However, differential privacy does not translate intuitively to disclosure risk. In particular, it remains unclear how much an adversary's belief about an individual's inclusion in a dataset can change after observing a protect...