| Fairness-aware agnostic federated learning W Du, D Xu, X Wu, H Tong Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021 | 127 | 2021 |
| Removing disparate impact on model accuracy in differentially private stochastic gradient descent D Xu, W Du, X Wu Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 60* | 2021 |
| Fair and robust classification under sample selection bias W Du, X Wu Proceedings of the 30th ACM International Conference on Information …, 2021 | 36* | 2021 |
| Poisoning attacks on fair machine learning MH Van, W Du, X Wu, A Lu International Conference on Database Systems for Advanced Applications, 370-386, 2022 | 25 | 2022 |
| Privacy-preserving multiparty learning for logistic regression W Du, A Li, Q Li International Conference on Security and Privacy in Communication Systems …, 2018 | 20 | 2018 |
| Approximate to be great: Communication efficient and privacy-preserving large-scale distributed deep learning in Internet of Things W Du, A Li, P Zhou, Z Xu, X Wang, H Jiang, D Wu IEEE internet of things Journal 7 (12), 11678-11692, 2020 | 17 | 2020 |
| Efficient federated learning via variational dropout W Du, X Zeng, M Yan, M Zhang | 13 | 2018 |
| Efficient privacy-preserving outsourcing of large-scale convex separable programming for smart cities W Liao, W Du, S Salinas, P Li 2016 IEEE 18th International Conference on High Performance Computing and …, 2016 | 12 | 2016 |
| Privacyeye: A privacy-preserving and computationally efficient deep learning-based mobile video analytics system W Du, A Li, P Zhou, B Niu, D Wu IEEE Transactions on Mobile Computing 21 (9), 3263-3279, 2021 | 11 | 2021 |
| Massive maritime path planning: A contextual online learning approach P Zhou, W Zhao, J Li, A Li, W Du, S Wen IEEE Transactions on Cybernetics 51 (12), 6262-6273, 2020 | 8 | 2020 |
| Fair regression under sample selection bias W Du, X Wu, H Tong 2022 IEEE International Conference on Big Data (Big Data), 1435-1444, 2022 | 5 | 2022 |
| Politecamera: Respecting strangers’ privacy in mobile photographing A Li, W Du, Q Li Security and Privacy in Communication Networks: 14th International …, 2018 | 5 | 2018 |
| Privacy-preserving outsourcing of large-scale nonlinear programming to the cloud A Li, W Du, Q Li Security and Privacy in Communication Networks: 14th International …, 2018 | 5 | 2018 |
| Robust personalized federated learning under demographic fairness heterogeneity AN Carey, W Du, X Wu 2022 IEEE International Conference on Big Data (Big Data), 1425-1434, 2022 | 4 | 2022 |
| Advpl: Adversarial personalized learning W Du, X Wu 2020 IEEE 7th International Conference on Data Science and Advanced …, 2020 | 4 | 2020 |
| Secure and efficient outsourcing of large-scale nonlinear programming W Du, Q Li 2017 IEEE Conference on Communications and Network Security (CNS), 1-9, 2017 | 4 | 2017 |
| A framework to preserve user privacy for machine learning as a service B Niu, L Zhang, Y Chen, A Li, W Du, J Cao, F Li GLOBECOM 2020-2020 IEEE Global Communications Conference, 1-6, 2020 | 3 | 2020 |
| Privacy-preserving and secure cloud computing: A case of large-scale nonlinear programming W Du, A Li, Q Li, P Zhou IEEE Transactions on Cloud Computing 11 (1), 484-498, 2021 | 2 | 2021 |
| Compressing cross-lingual multi-task models at qualtrics D Campos, D Perry, S Joshi, Y Gambhir, W Du, Z Xing, A Colak Proceedings of the AAAI Conference on Artificial Intelligence 37 (13), 15661 …, 2023 | 1 | 2023 |
| Defending evasion attacks via adversarially adaptive training MH Van, W Du, X Wu, F Chen, A Lu 2022 IEEE International Conference on Big Data (Big Data), 1515-1524, 2022 | 1 | 2022 |
