Di Wang

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Jinhui XuProfessor of the State University of New York at BuffaloVerified email at buffalo.edu
Lijie HuKAUSTVerified email at kaust.edu.sa
Marco GaboardiBoston UniversityVerified email at bu.edu
Mengdi HuaiIowa State UniversityVerified email at iastate.edu
Yulian WuKing Abdullah University of Science and TechnologyVerified email at kaust.edu.sa
Hanshen XiaoMITVerified email at mit.edu
Adam SmithProfessor of Computer Science, Boston UniversityVerified email at bu.edu
Chenglin MiaoAssistant Professor of Computer Science, Iowa State UniversityVerified email at iastate.edu
Aidong Zhang, Fellow of ACM, IEEE, a...Thomas M. Linville Professor of Computer Science, University of VirginiaVerified email at virginia.edu
Youming TaoTechnische Universität Berlin & Shandong UniversityVerified email at tkn.tu-berlin.de
Huanyu ZhangMetaVerified email at cornell.edu
Miao PanAssociate Professor of Electrical and Computer Engineering, University of HoustonVerified email at uh.edu
Srinivas DevadasEdwin Sibley Webster Professor of Electrical Engineering and Computer Science, MITVerified email at mit.edu
Shi LiProfessor, Nanjing UniversityVerified email at nju.edu.cn
Chen ChangyouAssistant Professor at University at BuffaloVerified email at buffalo.edu
Michael Kwok-Po NgSIAM Fellow, AAIA Fellow, Dean of Science, Chair Professor in Mathematics & in Data Science, HKBUVerified email at hkbu.edu.hk
Jiahao DingApplied Scientist, AmazonVerified email at amazon.com
Peng ZhaoNanjing UniversityVerified email at lamda.nju.edu.cn
Xiangyu GuoFacebook, University at BuffaloVerified email at buffalo.edu
Baochun LiProfessor of Electrical and Computer Engineering, University of TorontoVerified email at ece.toronto.edu

Di Wang

King Abdullah University of Science and Technology

Verified email at kaust.edu.sa - Homepage

Differential Privacy Fairness Robust Estimation


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Differentially private empirical risk minimization revisited: Faster and more general D Wang, M Ye, J Xu Advances in Neural Information Processing Systems 30, 2017	274	2017
Differentially private empirical risk minimization with non-convex loss functions D Wang, C Chen, J Xu International Conference on Machine Learning, 6526-6535, 2019	82	2019
Empirical risk minimization in non-interactive local differential privacy revisited D Wang, M Gaboardi, J Xu Advances in Neural Information Processing Systems 31, 2018	65	2018
On sparse linear regression in the local differential privacy model D Wang, J Xu International Conference on Machine Learning, 6628-6637, 2019	49	2019
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	42	2020
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	35	2022
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	33	2019
Principal component analysis in the local differential privacy model D Wang, J Xu Theoretical computer science 809, 296-312, 2020	32	2020
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	31	2021
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	29	2020
Noninteractive locally private learning of linear models via polynomial approximations D Wang, A Smith, J Xu Algorithmic Learning Theory, 898-903, 2019	28*	2019
Detectllm: Leveraging log rank information for zero-shot detection of machine-generated text J Su, TY Zhuo, D Wang, P Nakov arXiv preprint arXiv:2306.05540, 2023	23	2023
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	23	2022
High dimensional statistical estimation under uniformly dithered one-bit quantization J Chen, CL Wang, MK Ng, D Wang IEEE Transactions on Information Theory, 2023	17	2023
Empirical risk minimization in the non-interactive local model of differential privacy D Wang, M Gaboardi, A Smith, J Xu Journal of machine learning research 21 (200), 1-39, 2020	15	2020
Fake news detectors are biased against texts generated by large language models J Su, TY Zhuo, J Mansurov, D Wang, P Nakov arXiv preprint arXiv:2309.08674, 2023	13	2023
Differentially Private Pairwise Learning Revisited Z Xue, S Yang, M Huai, D Wang IJCAI 2021, 2021	13	2021
Privacy-aware Synthesizing for Crowdsourced Data. M Huai, Di Wang 0015, C Miao, J Xu, A Zhang IJCAI, 2542-2548, 2019	13	2019
Inductive graph unlearning CL Wang, M Huai, D Wang 32nd USENIX Security Symposium (USENIX Security 23), 3205-3222, 2023	12	2023
Differentially private (gradient) expectation maximization algorithm with statistical guarantees D Wang, J Ding, L Hu, Z Xie, M Pan, J Xu arXiv preprint arXiv:2010.13520, 2020	12	2020

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