Следене
Di Wang
Заглавие
Позовавания
Позовавания
Година
Differentially private empirical risk minimization revisited: Faster and more general
D Wang, M Ye, J Xu
Advances in Neural Information Processing Systems 30, 2017
2422017
Differentially private empirical risk minimization with non-convex loss functions
D Wang, C Chen, J Xu
International Conference on Machine Learning, 6526-6535, 2019
712019
Empirical risk minimization in non-interactive local differential privacy revisited
D Wang, M Gaboardi, J Xu
Advances in Neural Information Processing Systems 31, 2018
552018
On sparse linear regression in the local differential privacy model
D Wang, J Xu
International Conference on Machine Learning, 6628-6637, 2019
382019
On differentially private stochastic convex optimization with heavy-tailed data
D Wang, H Xiao, S Devadas, J Xu
International Conference on Machine Learning, 10081-10091, 2020
372020
Differentially private empirical risk minimization with smooth non-convex loss functions: A non-stationary view
D Wang, J Xu
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 1182-1189, 2019
272019
Principal component analysis in the local differential privacy model
D Wang, J Xu
Theoretical computer science 809, 296-312, 2020
262020
Pairwise learning with differential privacy guarantees
M Huai, D Wang, C Miao, J Xu, A Zhang
Proceedings of the AAAI Conference on Artificial Intelligence 34 (01), 694-701, 2020
232020
High dimensional differentially private stochastic optimization with heavy-tailed data
L Hu, S Ni, H Xiao, D Wang
Proceedings of the 41st ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of …, 2022
222022
Noninteractive locally private learning of linear models via polynomial approximations
D Wang, A Smith, J Xu
Algorithmic Learning Theory, 898-903, 2019
22*2019
Estimating smooth glm in non-interactive local differential privacy model with public unlabeled data
D Wang, H Zhang, M Gaboardi, J Xu
Algorithmic Learning Theory, 1207-1213, 2021
192021
Optimal rates of (locally) differentially private heavy-tailed multi-armed bandits
Y Tao, Y Wu, P Zhao, D Wang
International Conference on Artificial Intelligence and Statistics, 1546-1574, 2022
182022
Privacy-aware Synthesizing for Crowdsourced Data.
M Huai, Di Wang 0015, C Miao, J Xu, A Zhang
IJCAI, 2542-2548, 2019
122019
Empirical risk minimization in the non-interactive local model of differential privacy
D Wang, M Gaboardi, A Smith, J Xu
The Journal of Machine Learning Research 21 (1), 8282-8320, 2020
112020
Differentially Private Pairwise Learning Revisited
Z Xue, S Yang, M Huai, D Wang
IJCAI 2021, 2021
102021
Facility location problem in differential privacy model revisited
Y Esencayi, M Gaboardi, S Li, D Wang
Advances in neural information processing systems 32, 2019
102019
Differentially private sparse inverse covariance estimation
D Wang, M Huai, J Xu
2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2018
102018
High Dimensional Statistical Estimation under Uniformly Dithered One-bit Quantization
J Chen, CL Wang, MK Ng, D Wang
arXiv preprint arXiv:2202.13157, 2022
72022
High dimensional sparse linear regression under local differential privacy: Power and limitations
D Wang, A Smith, J Xu
2018 NIPS workshop in Privacy-Preserving Machine Learning 235, 2018
72018
Inferring ground truth from crowdsourced data under local attribute differential privacy
D Wang, J Xu
Theoretical Computer Science 865, 85-98, 2021
62021
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