differential privacy

Private k-Means Clustering with Stability Assumptions AISTATS 2020 Private-kNN: Practical Differential Privacy for Computer Vision CVPR 2020 Private Learning of Halfspaces: Simplifying the Construction and Reducing the Sample Complexity NeurIPS 2020 Privately Answering Classification Queries in the Agnostic PAC Model ALT 2020 Privately detecting changes in unknown distributions ICML 2020 Privately Learning Markov Random Fields ICML 2020 Privately Learning Thresholds: Closing the Exponential Gap COLT 2020 Private Mean Estimation of Heavy-Tailed Distributions COLT 2020 Private Protocols for U-Statistics in the Local Model and Beyond AISTATS 2020 Private Query Release Assisted by Public Data ICML 2020 Reasoning About Generalization via Conditional Mutual Information COLT 2020 Robust anomaly detection and backdoor attack detection via differential privacy ICLR 2020 Scalable Differential Privacy with Certified Robustness in Adversarial Learning ICML 2020 Selling Data at an Auction under Privacy Constraints UAI 2020 Smoothed Analysis of Online and Differentially Private Learning NeurIPS 2020 Smoothly Bounding User Contributions in Differential Privacy NeurIPS 2020 Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses NeurIPS 2020 Synthetic Data Generators -- Sequential and Private NeurIPS 2020 The Discrete Gaussian for Differential Privacy NeurIPS 2020 The Flajolet-Martin Sketch Itself Preserves Differential Privacy: Private Counting with Minimal Space NeurIPS 2020 The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks CVPR 2020 Towards Better Generalization of Adaptive Gradient Methods NeurIPS 2020 Towards practical differentially private causal graph discovery NeurIPS 2020 Understanding Gradient Clipping in Private SGD: A Geometric Perspective NeurIPS 2020 Variational Bayes in Private Settings (VIPS) (Extended Abstract) IJCAI 2020