方班隐私保护小组

2022年11月25日

【五期杨志】CCF-A (KDD'20) Multimodal Learning with Incomplete Modalities by Knowledge Distillation

摘要： Wang Q, Zhan L, Thompson P, et al. Multimodal learning with incomplete modalities by knowledge distillation[C]//Proceedings of the 26th ACM SIGKDD Int 阅读全文

posted @ 2022-11-25 22:08 方班隐私保护小组阅读(99) 评论(0) 推荐(0) 编辑

【五期李伟平】CCF-C(CC'19)privacy preserving distributed machine learning with federated learning

摘要： M.A.P.Chamikara, P.Bertok, I.Khalil, D.Liu, S.Camtepe. Privacy Preserving Distributed Machine Learning with Federated Learning. Computer Communication 阅读全文

posted @ 2022-11-25 21:43 方班隐私保护小组阅读(87) 评论(0) 推荐(0) 编辑

【五期邵润东】arXiv(22) No free lunch theorem for security and utility in federated learning

摘要： Xiaojin Zhang, Hanlin Gu, Lixin Fan, Kai Chen, and Qiang Yang. 2022. No free lunch theorem for security and utility in federated learning. 1, 1 (Septe 阅读全文

posted @ 2022-11-25 18:45 方班隐私保护小组阅读(71) 评论(0) 推荐(0) 编辑

2022年11月21日

【四期陶富强】CCF-B(Pattern Recognition12)Feature evaluation and selection with cooperative game theory

摘要： Sun X, Liu Y, Li J, et al. Feature evaluation and selection with cooperative game theory[J]. Pattern recognition, 2012, 45(8): 2992-3002. 这篇论文针对在机器学习训阅读全文

posted @ 2022-11-21 21:13 方班隐私保护小组阅读(77) 评论(1) 推荐(0) 编辑

2022年11月19日

【五期邵润东】CCF-A(TITF'20) VerifyNet: Secure and Verifiable Federated Learning

摘要： Xu, Guowen, et al. "Verifynet: Secure and verifiable federated learning." IEEE Transactions on Information Forensics and Security 15 (2019): 911-926. 阅读全文

posted @ 2022-11-19 17:11 方班隐私保护小组阅读(210) 评论(0) 推荐(0) 编辑

2022年11月18日

【五期邹昱夫】arXiv（IJCAI'22）Fedcg: Leverage conditional gan for protecting privacy and maintaining competitive performance in federated learning

摘要： International Joint Conferences on Artificial Intelligence 微众银行AI团队和中山大学合作发表的论文《FedCG：利用条件生成对抗网络在联邦学习中保护隐私并保持模型性能》提出了"FedCG"，将条件生成对抗网络（cGAN）与分割学习相结合，实阅读全文

posted @ 2022-11-18 21:11 方班隐私保护小组阅读(206) 评论(1) 推荐(0) 编辑

2022年11月10日

【五期-伍捷威】CCF-A（KDD'22）FedMSplit: Correlation-Adaptive Federated Multi-Task Learning across Multimodal Split Networks

摘要： Jiayi Chen and Aidong Zhang. 2022. FedMSplit: Correlation-Adaptive Federated Multi-Task Learning across Multimodal Split Networks. In Proceedings of t 阅读全文

posted @ 2022-11-10 22:51 方班隐私保护小组阅读(157) 评论(0) 推荐(0) 编辑

【五期梁锐】CCF-A, （TPDS'20）Towards Fair and Privacy-Preserving Federated Deep Models

摘要： L. Lyu et al., "Towards Fair and Privacy-Preserving Federated Deep Models," in IEEE Transactions on Parallel and Distributed Systems, vol. 31, no. 11, 阅读全文

posted @ 2022-11-10 18:24 方班隐私保护小组阅读(79) 评论(0) 推荐(0) 编辑

【五期李伟平】（IOTJ'19）Incentive_Mechanism_for_Reliable_Federated_Learning_A_Joint_Optimization_Approach_to_Combining_Reputation_and_Contract_Theory

摘要： Jiawen Kang,Zehui Xiong, Dusit Niyato, Shengli Xie, Junshan Zhang. Incentive Mechanism for Reliable Federated Learning A Joint Optimization Approach t 阅读全文

posted @ 2022-11-10 16:54 方班隐私保护小组阅读(57) 评论(0) 推荐(0) 编辑

【五期邹昱夫】 CCF-A(SP'22)Property Inference from Poisoning.

摘要： Mahloujifar, Saeed, Esha Ghosh, and Melissa Chase. "Property Inference from Poisoning." 2022 IEEE Symposium on Security and Privacy (SP). IEEE Compute 阅读全文

posted @ 2022-11-10 16:32 方班隐私保护小组阅读(159) 评论(0) 推荐(0) 编辑

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