Di Wang, Hanshen Xiao, Srini Devadas, and Jinhui Xu. "On Differentially Private Stochatsic Optimization with Heavy-tailed Data" In International Conference on Machine Learning. 2020.

Di Wang, Changyou Chen, and Jinhui Xu. "Differentially private empirical risk minimization with non-convex loss functions." In International Conference on Machine Learning, pp. 6526-6535. 2019.

Di Wang, and Jinhui Xu. "On sparse linear regression in the local differential privacy model." In International Conference on Machine Learning, pp. 6628-6637. 2019.

Di Wang, Marco Gaboardi, and Jinhui Xu. "Empirical risk minimization in non-interactive local differential privacy revisited." In Advances in Neural Information Processing Systems, pp. 965-974. 2018.

Di Wang, Minwei Ye, and Jinhui Xu. "Differentially private empirical risk minimization revisited: Faster and more general." In Advances in Neural Information Processing Systems, pp. 2722-2731. 2017.