Di Wang
TitleCited byYear
Differentially private empirical risk minimization revisited: Faster and more general
D Wang, M Ye, J Xu
Advances in Neural Information Processing Systems, 2722-2731, 2017
352017
Empirical Risk Minimization in Non-interactive Local Differential Privacy Revisited
D Wang, M Gaboardi, J Xu
Advances in Neural Information Processing Systems, 2018
18*2018
Noninteractive Locally Private Learning of Linear Models via Polynomial Approximations
D Wang, A Smith, J Xu
Algorithmic Learning Theory, 897-902, 2019
9*2019
Differentially private empirical risk minimization with smooth nonconvex loss functions: A non-stationary view
D Wang, J Xu
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
42019
Differentially Private Sparse Inverse Covariance Estimation
D Wang, M Huai, J Xu
2018 6th IEEE Global Conference on Signal and Information Processing, 2018
42018
Differentially Private Empirical Risk Minimization with Non-convex Loss Functions
D Wang, C Chen, J Xu
36th International Conference on Machine Learning, 2019
32019
Principal Component Analysis in the Local Differential Privacy Model
D Wang, J Xu
28th International Joint Conference on Artificial Intelligence, 2019
22019
High Dimensional Sparse Linear Regression under Local Differential Privacy: Power and Limitations
D Wang, A Smith, J Xu
NeurIPS 2018 Workshop on Privacy Preserving Machine Learning, 2018
22018
Large Scale Constrained Linear Regression Revisited: Faster Algorithms via Preconditioning
D Wang, J Xu
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence …, 2018
22018
Estimating Smooth GLM in Non-interactive Local Differential Privacy Model with Public Unlabeled Data
D Wang, H Zhang, M Gaboardi, J Xu
arXiv preprint arXiv:1910.00482, 2019
12019
Faster constrained linear regression via two-step preconditioning
D Wang, J Xu
Neurocomputing 364, 280-296, 2019
2019
Facility Location Problem in Differential Privacy Model Revisited
Y Esencayi, M Gaboardi, S Li, D Wang
arXiv preprint arXiv:1910.12050, 2019
2019
Flowless: Extracting Densest Subgraphs Without Flow Computations
D Boob, Y Gao, R Peng, S Sawlani, CE Tsourakakis, D Wang, J Wang
arXiv preprint arXiv:1910.07087, 2019
2019
Faster width-dependent algorithm for mixed packing and covering LPs
D Boob, S Sawlani, D Wang
arXiv preprint arXiv:1909.12387, 2019
2019
On Sparse Linear Regression in the Local Differential Privacy Model
D Wang, J Xu
International Conference on Machine Learning, 6628-6637, 2019
2019
Differentially Private High Dimensional Sparse Covariance Matrix Estimation
D Wang, J Xu
2019 53rd Annual Conference on Information Sciences, 2019
2019
Lower Bound of Locally Differentially Private Sparse Covariance Matrix Estimation
D Wang, J Xu
28th International Joint Conference on Artificial Intelligence, 2019
2019
Privacy-aware Synthesizing for Crowdsourced Data
M Huai, D Wang, C Miao, J Xu, A Zhang
28th International Joint Conference on Artificial Intelligence, 2019
2019
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