Zihang Xiang

According to our database, Zihang Xiang authored at least 7 papers between 2023 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Has Approximate Machine Unlearning been evaluated properly? From Auditing to Side Effects.

Cheng-Long Wang, Qi Li, Zihang Xiang, Di Wang

CoRR, 2024

How Does Selection Leak Privacy: Revisiting Private Selection and Improved Results for Hyper-parameter Tuning.

Zihang Xiang, Chenglong Wang, Di Wang

CoRR, 2024

Preserving Node-level Privacy in Graph Neural Networks.

Zihang Xiang, Tianhao Wang, Di Wang

Proceedings of the IEEE Symposium on Security and Privacy, 2024

2023

Practical Differentially Private and Byzantine-resilient Federated Learning.

Zihang Xiang, Tianhao Wang, Wanyu Lin, Di Wang

Proc. ACM Manag. Data, 2023

Differentially Private Non-convex Learning for Multi-layer Neural Networks.

Hanpu Shen, Cheng-Long Wang, Zihang Xiang, Yiming Ying, Di Wang

CoRR, 2023

A Theory to Instruct Differentially-Private Learning via Clipping Bias Reduction.

Hanshen Xiao, Zihang Xiang, Di Wang, Srinivas Devadas

Proceedings of the 44th IEEE Symposium on Security and Privacy, 2023

Privacy-preserving Sparse Generalized Eigenvalue Problem.

Lijie Hu, Zihang Xiang, Jiabin Liu, Di Wang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023