Published in Neural Networks, 2023
(GNN) This paper is about graph neural networks.
Recommended citation: Bisheng, Tang. (2023). "Generalized heterophily graph data augmentation for node classification." Neural Networks.
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Published in IEEE Transactions on Information Forensics and Security, 2023
(MPC) This paper is about the private binary Neural Network inference.
Recommended citation: Ye, Dong. (2023). "FlexBNN: Fast Private Binary Neural Network Inference With Flexible Bit-Width." IEEE Transactions on Information Forensics and Security.
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Published in ECCV2024,Preprint, 2024
(AI Security) This paper is about secure inference for Diffusion Model sampling.
Recommended citation: Xin, Zhao. (2024). "CipherDM: Secure Three-Party Inference for Diffusion Model Sampling." ECCV2024.
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Published in ICPP2024, 2024
(Graph) This paper is about Graph Federated Learning.
Recommended citation: Bisheng, Tang. (2024). "Graph Federated Learning with Center Moment Constraints for Node Classification." ICPP2024.
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Published in ICC2024, 2024
(MPC) This paper is about the secure inference.
Recommended citation: Xudong, Chen. (2024). "Roger: A Round Optimized GPU-Friendly Secure Inference Framework." ICC2024.
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Published in ICC2024, 2024
(MPC) This paper is about the secure Neural Network inference.
Recommended citation: Tingyu, Fan. (2024). "COMET: Communication-Efficient Batch Secure Three-Party Neural Network Inference with Client-Aiding." ICC2024.
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Published in ECAI2023, 2023
(Federated Learning) This paper is about the graph personalized Federated Learning.
Recommended citation: Xiaoying, Li. (2023). "Unsupervised Graph Structure-Aided Personalized Federated Learning ." ECAI2023.
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Published in ECML 2023, 2023
(Backdoor Attacks) This paper is about the backdoor attacks.
Recommended citation: Yuexin, Xuan. (2023). "Practical and General Backdoor Attacks against Vertical Federated Learning ." ECML 2023.
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Published in ECML-PKDD2022, 2023
(Knowledge Distillation) This paper is about the Machine Learning and Knowledge Discovery in Databases.
Recommended citation: Shaopu, Wang. (2022). "PrUE: Distilling Knowledge from Sparse Teacher Networks." ECML-PKDD2022.
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Published in WWW2023, 2023
(MPC) This paper is about the Neural Network inference.
Recommended citation: Ye, Dong. (2023). "Meteor: Improved Secure 3-Party Neural Network Inference with Reducing Online Communication Costs." WWW2023.
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Published in IJCNN2022, 2022
(Backdoor Attacks) This paper is about defense methods against backdoor attacks.
Recommended citation: Yuexin, Xuan. (2022). "ACTSS: Input Detection Defense against Backdoor Attacks via Activation Subset Scanning." IJCNN2022.
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Published in IJCNN2022, 2022
(GNN) This paper is about Graph Neural Networks.
Recommended citation: Bisheng, Tang. (2022). "KAFNN: A Knowledge Augmentation Framework to Graph Neural Networks." IJCNN2022.
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Published in IJCNN2022, 2022
(GNN) This paper is about graph neural networks.
Recommended citation: Bisheng, Tang. (2023). "Rethinking the Feature Iteration Process of Graph Convolution Networks." IJCNN2022.
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Published in CVPR2022, 2022
(Backdoor Attacks) This paper is about the backdoor attacks.
Recommended citation: Zhendong, Zhao. (2022). "DEFEAT: Deep Hidden Feature Backdoor Attacks by Imperceptible Perturbation and Latent Representation Constraints." CVPR2022.
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Published in ESORICS 2021, 2021
(MPC) This paper is about the private inference for Federated Learning.
Recommended citation: Ye, Dong. (2023). "FLOD:Oblivious Defender for Private Byzantine-Robust Federated Learning with Dishonest-Majority." ESORICS 2021.
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