differential privacy

Private and polynomial time algorithms for learning Gaussians and beyond COLT 2022 Private Convex Optimization via Exponential Mechanism COLT 2022 Private Estimation with Public Data NeurIPS 2022 Private frequency estimation via projective geometry ICML 2022 Private Graph All-Pairwise-Shortest-Path Distance Release with Improved Error Rate NeurIPS 2022 Private High-Dimensional Hypothesis Testing COLT 2022 Private Isotonic Regression NeurIPS 2022 PrivateMail: Supervised Manifold Learning of Deep Features with Privacy for Image Retrieval AAAI 2022 Private Matrix Approximation and Geometry of Unitary Orbits COLT 2022 Private optimization in the interpolation regime: faster rates and hardness results ICML 2022 Private Rank Aggregation in Central and Local Models AAAI 2022 Private Robust Estimation by Stabilizing Convex Relaxations COLT 2022 Private Semi-Supervised Federated Learning IJCAI 2022 Private Sequential Hypothesis Testing for Statisticians: Privacy, Error Rates, and Sample Size AISTATS 2022 Private Set Generation with Discriminative Information NeurIPS 2022 Private Streaming SCO in ℓ_p geometry with Applications in High Dimensional Online Decision Making ICML 2022 Private Synthetic Data for Multitask Learning and Marginal Queries NeurIPS 2022 Privid: Practical, Privacy-Preserving Video Analytics Queries NSDI 2022 Provably Confidential Language Modelling NAACL 2022 Public Data-Assisted Mirror Descent for Private Model Training ICML 2022 Re-Analyze Gauss: Bounds for Private Matrix Approximation via Dyson Brownian Motion NeurIPS 2022 Recovering Private Text in Federated Learning of Language Models NeurIPS 2022 Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data ICML 2022 Sample-and-threshold differential privacy: Histograms and applications AISTATS 2022 SASH: Efficient secure aggregation based on SHPRG for federated learning UAI 2022