Zihang Xiang - RankMe

23 papers A* 5A 1Journal 16Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition. CoRR Difei Xu, Meng Ding, Zihang Xiang, Jinhui Xu, Di Wang
2025	J	`jnl`	Beyond ordinary Lipschitz constraints: Differentially Private optimization with TNC. Trans. Mach. Learn. Res. Difei Xu, Meng Ding, Zihang Xiang, Jinhui Xu, Di Wang
2025	—	`conf`	Differentially Private Sparse Linear Regression with Heavy-Tailed Responses. ECML/PKDD (5) Xizhi Tian, Meng Ding, Touming Tao, Zihang Xiang, Di Wang
2025	J	`jnl`	Differentially Private Sparse Linear Regression with Heavy-tailed Responses. CoRR Xizhi Tian, Meng Ding, Touming Tao, Zihang Xiang, Di Wang
2025	J	`jnl`	FlashDP: Private Training Large Language Models with Efficient DP-SGD. CoRR Liangyu Wang, Junxiao Wang, Jie Ren, Zihang Xiang, David E. Keyes, Di Wang
2025	A*	`conf`	Improved Rates of Differentially Private Nonconvex-Strongly-Concave Minimax Optimization. AAAI Ruijia Zhang, Mingxi Lei, Meng Ding, Zihang Xiang, Jinhui Xu, Di Wang
2025	J	`jnl`	Improved Rates of Differentially Private Nonconvex-Strongly-Concave Minimax Optimization. CoRR Ruijia Zhang, Mingxi Lei, Meng Ding, Zihang Xiang, Jinhui Xu, Di Wang
2025	A*	`conf`	Privacy Audit as Bits Transmission: (Im)possibilities for Audit by One Run. USENIX Security Symposium Zihang Xiang, Tianhao Wang, Di Wang
2025	J	`jnl`	Privacy Audit as Bits Transmission: (Im)possibilities for Audit by One Run. CoRR Zihang Xiang, Tianhao Wang, Di Wang
2025	J	`jnl`	Tight Privacy Audit in One Run. CoRR Zihang Xiang, Tianhao Wang, Hanshen Xiao, Yuan Tian, Di Wang
2025	A*	`conf`	Towards Lifecycle Unlearning Commitment Management: Measuring Sample-level Unlearning Completeness. USENIX Security Symposium Cheng-Long Wang, Qi Li, Zihang Xiang, Yinzhi Cao, Di Wang
2025	J	`jnl`	Towards Lifecycle Unlearning Commitment Management: Measuring Sample-level Unlearning Completeness. CoRR Cheng-Long Wang, Qi Li, Zihang Xiang, Yinzhi Cao, Di Wang
2025	J	`jnl`	Towards User-level Private Reinforcement Learning with Human Feedback. CoRR Jiaming Zhang, Mingxi Lei, Meng Ding, Mengdi Li, Zihang Xiang, Difei Xu, Jinhui Xu, Di Wang
2024	J	`jnl`	Has Approximate Machine Unlearning been evaluated properly? From Auditing to Side Effects. CoRR Cheng-Long Wang, Qi Li, Zihang Xiang, Di Wang
2024	J	`jnl`	How Does Selection Leak Privacy: Revisiting Private Selection and Improved Results for Hyper-parameter Tuning. CoRR Zihang Xiang, Cheng-Long Wang, Di Wang
2024	J	`jnl`	Nearly Optimal Rates of Privacy-Preserving Sparse Generalized Eigenvalue Problem. IEEE Trans. Knowl. Data Eng. Lijie Hu, Zihang Xiang, Jiabin Liu, Di Wang
2024	A*	`conf`	Preserving Node-level Privacy in Graph Neural Networks. SP Zihang Xiang, Tianhao Wang, Di Wang
2023	A*	`conf`	A Theory to Instruct Differentially-Private Learning via Clipping Bias Reduction. SP Hanshen Xiao, Zihang Xiang, Di Wang, Srinivas Devadas
2023	J	`jnl`	Differentially Private Non-convex Learning for Multi-layer Neural Networks. CoRR Hanpu Shen, Cheng-Long Wang, Zihang Xiang, Yiming Ying, Di Wang
2023	J	`jnl`	Practical Differentially Private and Byzantine-resilient Federated Learning. CoRR Zihang Xiang, Tianhao Wang, Wanyu Lin, Di Wang
2023	J	`jnl`	Practical Differentially Private and Byzantine-resilient Federated Learning. Proc. ACM Manag. Data Zihang Xiang, Tianhao Wang, Wanyu Lin, Di Wang
2023	J	`jnl`	Preserving Node-level Privacy in Graph Neural Networks. CoRR Zihang Xiang, Tianhao Wang, Di Wang
2023	A	`conf`	Privacy-preserving Sparse Generalized Eigenvalue Problem. AISTATS Lijie Hu, Zihang Xiang, Jiabin Liu, Di Wang