Security & Privacy

Elliptical Perturbations for Differential Privacy NeurIPS 2019 Facility Location Problem in Differential Privacy Model Revisited NeurIPS 2019 How Does Knowledge of the AUC Constrain the Set of Possible Ground-Truth Labelings? AAAI 2019 KNG: The K-Norm Gradient Mechanism NeurIPS 2019 Limits of Private Learning with Access to Public Data NeurIPS 2019 Locally Private Gaussian Estimation NeurIPS 2019 Logistic Regression on Homomorphic Encrypted Data at Scale AAAI 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 Amplification by Mixing and Diffusion Mechanisms NeurIPS 2019 Privacy-Preserving Classification of Personal Text Messages with Secure Multi-Party Computation NeurIPS 2019 Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces NeurIPS 2019 Privacy-Preserving Speaker Recognition with Cohort Score Normalisation Interspeech 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 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 Sensitive-Sample Fingerprinting of Deep Neural Networks CVPR 2019