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A Pragmatic Approach to Membership Inferences on Machine Learning Models.

Y. Long, L. Wang, D. Bu, V. Bindschaedler, X. Wang, H. Tang, C. Gunter, и K. Chen. EuroS&P, стр. 521-534. IEEE, (2020)

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Yunhui Hou

Yunhui Wang

Long Chen

Long Ling

Li Long

Другие публикации лиц с тем же именем

Understanding and mitigating privacy risk in machine learning systemsY. Long. University of Illinois Urbana-Champaign, USA, (2020)SoK: Privacy-Preserving Data Synthesis.Y. Hu, F. Wu, Q. Li, Y. Long, G. Garrido, C. Ge, B. Ding, D. Forsyth, B. Li, и D. Song. CoRR, (2023)SecretGen: Privacy Recovery on Pre-trained Models via Distribution Discrimination.Z. Yuan, F. Wu, Y. Long, C. Xiao, и B. Li. ECCV (5), том 13665 из Lecture Notes in Computer Science, стр. 139-155. Springer, (2022)BEEER: distributed record and replay for medical devices in hospital operating rooms.A. Hojjati, Y. Long, S. Demetriou, и C. Gunter. HotSoS, стр. 1:1-1:10. ACM, (2019)Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks.C. Xie, Y. Long, P. Chen, Q. Li, S. Koyejo, и B. Li. CCS, стр. 1511-1525. ACM, (2023)DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation.B. Wang, F. Wu, Y. Long, L. Rimanic, C. Zhang, и B. Li. CCS, стр. 2146-2168. ACM, (2021)A Pragmatic Approach to Membership Inferences on Machine Learning Models.Y. Long, L. Wang, D. Bu, V. Bindschaedler, X. Wang, H. Tang, C. Gunter, и K. Chen. EuroS&P, стр. 521-534. IEEE, (2020)Uncovering the Connection Between Differential Privacy and Certified Robustness of Federated Learning against Poisoning Attacks.C. Xie, Y. Long, P. Chen, и B. Li. CoRR, (2022)LINKTELLER: Recovering Private Edges from Graph Neural Networks via Influence Analysis.F. Wu, Y. Long, C. Zhang, и B. Li. SP, стр. 2005-2024. IEEE, (2022)Understanding Membership Inferences on Well-Generalized Learning Models.Y. Long, V. Bindschaedler, L. Wang, D. Bu, X. Wang, H. Tang, C. Gunter, и K. Chen. CoRR, (2018)

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