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Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks.

, , , , , and . CCS, page 1511-1525. ACM, (2023)

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SoK: Privacy-Preserving Data Synthesis., , , , , , , , , and . CoRR, (2023)SecretGen: Privacy Recovery on Pre-trained Models via Distribution Discrimination., , , , and . ECCV (5), volume 13665 of Lecture Notes in Computer Science, page 139-155. Springer, (2022)Understanding and mitigating privacy risk in machine learning systems. University of Illinois Urbana-Champaign, USA, (2020)DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation., , , , , and . CCS, page 2146-2168. ACM, (2021)Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks., , , , , and . CCS, page 1511-1525. ACM, (2023)Towards Measuring Membership Privacy., , and . CoRR, (2017)BEEER: distributed record and replay for medical devices in hospital operating rooms., , , and . HotSoS, page 1:1-1:10. ACM, (2019)A Pragmatic Approach to Membership Inferences on Machine Learning Models., , , , , , , and . EuroS&P, page 521-534. IEEE, (2020)Understanding Membership Inferences on Well-Generalized Learning Models., , , , , , , and . CoRR, (2018)Distributed and Secure ML with Self-tallying Multi-party Aggregation., , , and . CoRR, (2018)