Privacy

Privacy-Preserving Gaussian Process Regression – A Modular Approach to the Application of Homomorphic Encryption AAAI 2020 Privacy-Preserving Gradient Boosting Decision Trees AAAI 2020 Privacy-Preserving News Recommendation Model Learning EMNLP 2020 Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead ICML 2020 Private Identity Testing for High-Dimensional Distributions NeurIPS 2020 Private k-Means Clustering with Stability Assumptions AISTATS 2020 Private-kNN: Practical Differential Privacy for Computer Vision CVPR 2020 Private Learning of Halfspaces: Simplifying the Construction and Reducing the Sample Complexity NeurIPS 2020 Privately Answering Classification Queries in the Agnostic PAC Model ALT 2020 Privately detecting changes in unknown distributions ICML 2020 Privately Learning Markov Random Fields ICML 2020 Privately Learning Thresholds: Closing the Exponential Gap COLT 2020 Private Mean Estimation of Heavy-Tailed Distributions COLT 2020 Private Outsourced Bayesian Optimization ICML 2020 Private Protocols for U-Statistics in the Local Model and Beyond AISTATS 2020 Private Query Release Assisted by Public Data ICML 2020 Private Reinforcement Learning with PAC and Regret Guarantees ICML 2020 PrivNet: Safeguarding Private Attributes in Transfer Learning for Recommendation EMNLP 2020 Protecting Geolocation Privacy of Photo Collections AAAI 2020 Radioactive data: tracing through training ICML 2020 Robust anomaly detection and backdoor attack detection via differential privacy ICLR 2020 Robust Encodings: A Framework for Combating Adversarial Typos ACL 2020 Robust Federated Learning via Collaborative Machine Teaching AAAI 2020 Scalable Differential Privacy with Certified Robustness in Adversarial Learning ICML 2020 Selling Data at an Auction under Privacy Constraints UAI 2020