differential privacy

Private Non-smooth ERM and SCO in Subquadratic Steps NeurIPS 2021 Private optimization without constraint violations AISTATS 2021 Private Post-GAN Boosting ICLR 2021 Private Release of Text Embedding Vectors NAACL 2021 Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry ICML 2021 Private Stochastic Non-convex Optimization with Improved Utility Rates IJCAI 2021 Projection-Free Bandit Optimization with Privacy Guarantees AAAI 2021 Relaxed Marginal Consistency for Differentially Private Query Answering NeurIPS 2021 Remember What You Want to Forget: Algorithms for Machine Unlearning NeurIPS 2021 Revenue-Incentive Tradeoffs in Dynamic Reserve Pricing ICML 2021 Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning AISTATS 2021 Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning JMLR 2021 Robust and differentially private mean estimation NeurIPS 2021 Robust and Private Learning of Halfspaces AISTATS 2021 Scalable Differential Privacy With Sparse Network Finetuning CVPR 2021 Secure Deep Graph Generation with Link Differential Privacy IJCAI 2021 SGD with low-dimensional gradients with applications to private and distributed learning UAI 2021 Shuffled Model of Differential Privacy in Federated Learning AISTATS 2021 Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning NeurIPS 2021 Single and Multiple Change-Point Detection with Differential Privacy JMLR 2021 Stability and Differential Privacy of Stochastic Gradient Descent for Pairwise Learning with Non-Smooth Loss AISTATS 2021 Tempered Sigmoid Activations for Deep Learning with Differential Privacy AAAI 2021 The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation ICML 2021 The Skellam Mechanism for Differentially Private Federated Learning NeurIPS 2021 The Sparse Vector Technique, Revisited COLT 2021