differential privacy

Practical Differentially Private Top-k Selection with Pay-what-you-get Composition NeurIPS 2019 Privacy Amplification by Mixing and Diffusion Mechanisms NeurIPS 2019 Privacy-aware Synthesizing for Crowdsourced Data IJCAI 2019 Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces NeurIPS 2019 Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction IJCAI 2019 Private Center Points and Learning of Halfspaces COLT 2019 Private Hypothesis Selection NeurIPS 2019 Private Learning Implies Online Learning: An Efficient Reduction NeurIPS 2019 Privately Learning High-Dimensional Distributions COLT 2019 Private Model Compression via Knowledge Distillation AAAI 2019 Private Stochastic Convex Optimization with Optimal Rates NeurIPS 2019 Private Testing of Distributions via Sample Permutations NeurIPS 2019 Simultaneous Private Learning of Multiple Concepts JMLR 2019 Sublinear Space Private Algorithms Under the Sliding Window Model ICML 2019 Test without Trust: Optimal Locally Private Distribution Testing AISTATS 2019 Unified Sample-Optimal Property Estimation in Near-Linear Time NeurIPS 2019 Bounded-Loss Private Prediction Markets NeurIPS 2018 Calibrating Noise to Variance in Adaptive Data Analysis COLT 2018 Clustering Algorithms for the Centralized and Local Models ALT 2018 Corrupt Bandits for Preserving Local Privacy ALT 2018 cpSGD: Communication-efficient and differentially-private distributed SGD NeurIPS 2018 Data-dependent PAC-Bayes priors via differential privacy NeurIPS 2018 Differentially Private Bayesian Inference for Exponential Families NeurIPS 2018 Differentially Private Change-Point Detection NeurIPS 2018 Differentially Private Contextual Linear Bandits NeurIPS 2018