Security & Privacy

Differentially Private Correlation Clustering ICML 2021 Differentially Private Densest Subgraph Detection ICML 2021 Differentially Private Empirical Risk Minimization under the Fairness Lens NeurIPS 2021 Differentially Private k-Means via Exponential Mechanism and Max Cover AAAI 2021 Differentially Private Link Prediction with Protected Connections AAAI 2021 Differentially Private Multi-Armed Bandits in the Shuffle Model NeurIPS 2021 Differentially Private Nonparametric Regression Under a Growth Condition COLT 2021 Differentially Private Pairwise Learning Revisited IJCAI 2021 Differentially Private Quantiles ICML 2021 Differentially Private Sliced Wasserstein Distance ICML 2021 Differentially Private Stochastic Coordinate Descent AAAI 2021 Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning ICLR 2021 DP-MERF: Differentially Private Mean Embeddings with RandomFeatures for Practical Privacy-preserving Data Generation AISTATS 2021 Ensemble Attention Distillation for Privacy-Preserving Federated Learning ICCV 2021 Exact Privacy Guarantees for Markov Chain Implementations of the Exponential Mechanism with Artificial Atoms NeurIPS 2021 Fast and Memory Efficient Differentially Private-SGD via JL Projections NeurIPS 2021 Federated f-Differential Privacy AISTATS 2021 Federated Learning of User Verification Models Without Sharing Embeddings ICML 2021 Federated Model Distillation with Noise-Free Differential Privacy IJCAI 2021 FLAME: Differentially Private Federated Learning in the Shuffle Model AAAI 2021 Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix ICML 2021 Grey-box Extraction of Natural Language Models ICML 2021 HEMET: A Homomorphic-Encryption-Friendly Privacy-Preserving Mobile Neural Network Architecture ICML 2021 Hiding Numerical Vectors in Local Private and Shuffled Messages IJCAI 2021 How Does Data Augmentation Affect Privacy in Machine Learning? AAAI 2021