02 2023 档案
摘要：Panda R, Chen C F R, Fan Q, et al. Adamml: Adaptive multi-modal learning for efficient video recognition[C]//Proceedings of the IEEE/CVF International
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摘要："Liu, Yiyong, et al. "Membership inference attacks by exploiting loss trajectory." Proceedings of the 2022 ACM SIGSAC Conference on Computer and Commu
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摘要：Carion, Nicolas, et al. "End-to-end object detection with transformers." European conference on computer vision. Springer, Cham, 2020. 针对传统目标检测算法中存在的一
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摘要："Rezaei, Shahbaz, and Xin Liu. "On the difficulty of membership inference attacks." Proceedings of the IEEE/CVF Conference on Computer Vision and Patt
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摘要：Song, F. , et al. "Efficient and Secure k-Nearest Neighbor Search Over Encrypted Data in Public Cloud." ICC 2019 - 2019 IEEE International Conference
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摘要：Luo, et al. "Outlier-eliminated k-means clustering algorithm based on differential privacy preservation." Applied Intelligence the International Journ
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摘要："Nasr M, Songi S, Thakurta A, et al. Adversary instantiation: Lower bounds for differentially private machine learning[C]//2021 IEEE Symposium on secu
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摘要：Mugunthan, V. , A. Peraire-Bueno , and L. Kagal . "PrivacyFL: A simulator for privacy-preserving and secure federated learning.", 10.1145/3340531.3412
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摘要：Thapa, C. , M. Chamikara , and S. Camtepe . "SplitFed: When Federated Learning Meets Split Learning." (2020). 本文提出了一种联邦学习（FL）和分割学习（SL）的混合方法（SFL），能够同时解
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摘要："Jayaraman B, Evans D. Evaluating differentially private machine learning in practice[C]//USENIX Security Symposium. 2019." 本文对机器学习不同隐私机制进行评估。评估重点放在梯度
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摘要：Rothchild, Daniel, et al. "Fetchsgd: Communication-efficient federated learning with sketching." International Conference on Machine Learning. PMLR, 2
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摘要："Salem A, Wen R, Backes M, et al. Dynamic backdoor attacks against machine learning models[C]//2022 IEEE 7th European Symposium on Security and Privac
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摘要：Rindal, Peter , and P. Schoppmann . "VOLE-PSI: Fast OPRF and Circuit-PSI from Vector-OLE." 2021. 本文采用VOLE和PaXoS数据结构提出了一种批处理伪随机数函数OPRF的构造，并用其实现隐私交集PSI。
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摘要：Li, X. , R. Dowsley , and MD Cock. "Privacy-Preserving Feature Selection with Secure Multiparty Computation.", 10.48550/arXiv.2102.03517. 2021. 当前PPML
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摘要：Zhang, Michael, et al. "Personalized federated learning with first order model optimization." arXiv preprint arXiv:2012.08565 (2020). 本文是一篇2021年发表在ICR
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摘要："Song C, Shmatikov V. Auditing data provenance in text-generation models[C]//Proceedings of the 25th ACM SIGKDD International Conference on Knowledge
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