Differential Privacy

Online Local Differential Private Quantile Inference via Self-normalization ICML 2023 On Private and Robust Bandits NeurIPS 2023 On the Privacy-Robustness-Utility Trilemma in Distributed Learning ICML 2023 On User-Level Private Convex Optimization ICML 2023 Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models ICML 2023 Posthoc privacy guarantees for collaborative inference with modified Propose-Test-Release NeurIPS 2023 Practical Differentially Private Hyperparameter Tuning with Subsampling NeurIPS 2023 Privacy Auditing with One (1) Training Run NeurIPS 2023 Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design ICML 2023 Privacy Aware Question-Answering System for Online Mental Health Risk Assessment ACL 2023 Privacy-Aware Rejection Sampling JMLR 2023 Privacy-preserving Sparse Generalized Eigenvalue Problem AISTATS 2023 Private Covariance Approximation and Eigenvalue-Gap Bounds for Complex Gaussian Perturbations COLT 2023 Private Federated Frequency Estimation: Adapting to the Hardness of the Instance NeurIPS 2023 Private Statistical Estimation of Many Quantiles ICML 2023 Protecting Global Properties of Datasets with Distribution Privacy Mechanisms AISTATS 2023 Regression with Label Differential Privacy ICLR 2023 Secure Federated Correlation Test and Entropy Estimation ICML 2023 Simple Binary Hypothesis Testing under Local Differential Privacy and Communication Constraints COLT 2023 Statistical Theory of Differentially Private Marginal-based Data Synthesis Algorithms ICLR 2023 Stochastic Differentially Private and Fair Learning ICLR 2023 TAN Without a Burn: Scaling Laws of DP-SGD ICML 2023 The communication cost of security and privacy in federated frequency estimation AISTATS 2023 The Price of Differential Privacy under Continual Observation ICML 2023 The Saddle-Point Method in Differential Privacy ICML 2023