Manuscript
Manuscript
Chendi Wang and Xin Guo. Pairwise learning with Kronecker product kernels. Submitted, 2022.
Chendi Wang and Xin Guo. Pairwise learning with Kronecker product kernels. Submitted, 2022.
Xiang Li, Chendi Wang, Buxin Su, Qi Long, Weijie J. Su. Mitigating the Privacy–Utility Trade-off in Decentralized Federated Learning via f-Differential Privacy. NeurIPS (Spotlight). 2025.
Chendi Wang, Yuqing Zhu, Weijie J. Su, Yu-Xiang Wang. Neural Collapse meets differential privacy: Curious behaviors of NoisyGD with near-perfect representation learning. ICML (Oral Presentation), 2024.
Chendi Wang, Buxin Su, Jiayuan Ye, Reza Shokri, Weijie J. Su. Unified enhancement of privacy bounds for mixture mechanisms via f-differential privacy. NeurIPS, 2023.
Ximing Li, Chendi Wang, and Guang Cheng. Statistical theory of differentially private marginal-based data synthesis algorithms. ICLR , 2023.
Buxin Su, Weijie J. Su, Chendi Wang (alphabetical order). The 2020 United States Decennial Census Is More Private Than You (Might) Think. Proceedings of the National Academy of Sciences (PNAS), accepted, 2025.
Chendi Wang, Xin Guo, Qiang Wu. Learning with centered reproducing kernels. Analysis and Applications, 2024.
Shirong Xu, Chendi Wang, Will Wei Sun, and Guang Cheng. Binary Classification under Local Label Differential Privacy Using Randomized Response Mechanisms. Transactions on Machine Learning Research. 2023.
Chendi Wang. Modified Poisson estimators for grouped and right-censored counts. Communications in Statistics - Theory and Methods, 2021.