differential privacy

Bring Your Own Algorithm for Optimal Differentially Private Stochastic Minimax Optimization NeurIPS 2022 Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints NeurIPS 2022 Composition Theorems for Interactive Differential Privacy NeurIPS 2022 Data Augmentation MCMC for Bayesian Inference from Privatized Data NeurIPS 2022 Differentially Private Approximate Quantiles ICML 2022 Differentially Private Community Detection for Stochastic Block Models ICML 2022 Differentially Private Coordinate Descent for Composite Empirical Risk Minimization ICML 2022 Differentially Private Densest Subgraph AISTATS 2022 Differentially Private Estimation of Heterogeneous Causal Effects CLeaR 2022 Differentially Private Federated Learning on Heterogeneous Data AISTATS 2022 Differentially Private Federated Learning With Local Regularization and Sparsification CVPR 2022 Differentially Private Fine-tuning of Language Models ICLR 2022 Differentially Private Fractional Frequency Moments Estimation with Polylogarithmic Space ICLR 2022 Differentially Private Generalized Linear Models Revisited NeurIPS 2022 Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank NeurIPS 2022 Differentially Private Histograms under Continual Observation: Streaming Selection into the Unknown AISTATS 2022 Differentially Private Instance Encoding against Privacy Attacks NAACL 2022 Differentially Private Language Models for Secure Data Sharing EMNLP 2022 Differentially Private Learning Needs Hidden State (Or Much Faster Convergence) NeurIPS 2022 Differentially Private Learning with Margin Guarantees NeurIPS 2022 Differentially Private Linear Sketches: Efficient Implementations and Applications NeurIPS 2022 Differentially Private Maximal Information Coefficients ICML 2022 Differentially Private Model Compression NeurIPS 2022 Differentially private multi-party data release for linear regression UAI 2022 Differentially Private Normalizing Flows for Synthetic Tabular Data Generation AAAI 2022