Differential Privacy

Smoothed Analysis of Online and Differentially Private Learning NeurIPS 2020 Smoothly Bounding User Contributions in Differential Privacy NeurIPS 2020 The Discrete Gaussian for Differential Privacy NeurIPS 2020 An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors NeurIPS 2019 Capacity Bounded Differential Privacy NeurIPS 2019 Characterizing the Sample Complexity of Pure Private Learners JMLR 2019 Differentially Private Algorithms for Learning Mixtures of Separated Gaussians NeurIPS 2019 Differentially Private Anonymized Histograms NeurIPS 2019 Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate NeurIPS 2019 Differentially Private Bayesian Linear Regression NeurIPS 2019 Differentially Private Community Detection in Attributed Social Networks ACML 2019 Differentially Private Distributed Data Summarization under Covariate Shift NeurIPS 2019 Differentially Private Empirical Risk Minimization with Smooth Non-Convex Loss Functions: A Non-Stationary View AAAI 2019 Elliptical Perturbations for Differential Privacy NeurIPS 2019 Facility Location Problem in Differential Privacy Model Revisited NeurIPS 2019 KNG: The K-Norm Gradient Mechanism NeurIPS 2019 Locally Private Gaussian Estimation NeurIPS 2019 Lower Bound of Locally Differentially Private Sparse Covariance Matrix Estimation IJCAI 2019 Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases NeurIPS 2019 Oblivious Sampling Algorithms for Private Data Analysis NeurIPS 2019 On Differentially Private Graph Sparsification and Applications NeurIPS 2019 P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification CVPR 2019 PATE-GAN: Generating Synthetic Data with Differential Privacy Guarantees ICLR 2019 Practical Differentially Private Top-k Selection with Pay-what-you-get Composition NeurIPS 2019 Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces NeurIPS 2019