Privacy

Locally Private Learning without Interaction Requires Separation NeurIPS 2019 Locally Private Mean Estimation: Z-test and Tight Confidence Intervals AISTATS 2019 Logistic Regression on Homomorphic Encrypted Data at Scale AAAI 2019 Lower Bounds for Locally Private Estimation via Communication Complexity COLT 2019 Low Latency Privacy Preserving Inference ICML 2019 Making AI Forget You: Data Deletion in Machine Learning NeurIPS 2019 Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases NeurIPS 2019 Mitigating Information Leakage in Image Representations: A Maximum Entropy Approach CVPR 2019 Noninteractive Locally Private Learning of Linear Models via Polynomial Approximations ALT 2019 Novel Collaborative Filtering Recommender Friendly to Privacy Protection IJCAI 2019 Oblivious Sampling Algorithms for Private Data Analysis NeurIPS 2019 Old Techniques in Differentially Private Linear Regression ALT 2019 On Connecting Stochastic Gradient MCMC and Differential Privacy AISTATS 2019 On Differentially Private Graph Sparsification and Applications NeurIPS 2019 On Fair Cost Sharing Games in Machine Learning AAAI 2019 Online Learning via the Differential Privacy Lens NeurIPS 2019 On Privacy Protection of Latent Dirichlet Allocation Model Training IJCAI 2019 On Sparse Linear Regression in the Local Differential Privacy Model ICML 2019 Open Problem: Is Margin Sufficient for Non-Interactive Private Distributed Learning? COLT 2019 Optimal Noise-Adding Mechanism in Additive Differential Privacy AISTATS 2019 Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness Against Adversarial Attack CVPR 2019 Partially Encrypted Deep Learning using Functional Encryption NeurIPS 2019 Personalized Peer Truth Serum for Eliciting Multi-Attribute Personal Data UAI 2019 Poission Subsampled Rényi Differential Privacy ICML 2019 Practical Differentially Private Top-k Selection with Pay-what-you-get Composition NeurIPS 2019