Wei Du

According to our database, Wei Du authored at least 22 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Privacy-Preserving and Secure Cloud Computing: A Case of Large-Scale Nonlinear Programming.

Wei Du, Ang Li, Qinghua Li, Pan Zhou

IEEE Trans. Cloud Comput., 2023

A Robust Classifier under Missing-Not-at-Random Sample Selection Bias.

Huy Mai, Wen Huang, Wei Du, Xintao Wu

Proceedings of the IEEE International Conference on Big Data, 2023

2022

PrivacyEye: A Privacy-Preserving and Computationally Efficient Deep Learning-Based Mobile Video Analytics System.

Wei Du, Ang Li, Pan Zhou, Ben Niu, Dapeng Wu

IEEE Trans. Mob. Comput., 2022

Poisoning Attacks on Fair Machine Learning.

Minh-Hao Van, Wei Du, Xintao Wu, Aidong Lu

Proceedings of the Database Systems for Advanced Applications, 2022

Defending Evasion Attacks via Adversarially Adaptive Training.

Minh-Hao Van, Wei Du, Xintao Wu, Feng Chen, Aidong Lu

Proceedings of the IEEE International Conference on Big Data, 2022

Fair Regression under Sample Selection Bias.

Wei Du, Xintao Wu, Hanghang Tong

Proceedings of the IEEE International Conference on Big Data, 2022

Robust Personalized Federated Learning under Demographic Fairness Heterogeneity.

Alycia N. Carey, Wei Du, Xintao Wu

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Massive Maritime Path Planning: A Contextual Online Learning Approach.

Pan Zhou, Weiguang Zhao, Jianghui Li, Ang Li, Wei Du, Shiping Wen

IEEE Trans. Cybern., 2021

Enhancing personalized modeling via weighted and adversarial learning.

Wei Du, Xintao Wu

Int. J. Data Sci. Anal., 2021

Robust Fairness-aware Learning Under Sample Selection Bias.

Wei Du, Xintao Wu

CoRR, 2021

Fairness-aware Agnostic Federated Learning.

Wei Du, Depeng Xu, Xintao Wu, Hanghang Tong

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Removing Disparate Impact on Model Accuracy in Differentially Private Stochastic Gradient Descent.

Depeng Xu, Wei Du, Xintao Wu

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Fair and Robust Classification Under Sample Selection Bias.

Wei Du, Xintao Wu

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Approximate to Be Great: Communication Efficient and Privacy-Preserving Large-Scale Distributed Deep Learning in Internet of Things.

Wei Du, Ang Li, Pan Zhou, Zichuan Xu, Xiumin Wang, Hao Jiang, Dapeng Oliver Wu

IEEE Internet Things J., 2020

Removing Disparate Impact of Differentially Private Stochastic Gradient Descent on Model Accuracy.

Depeng Xu, Wei Du, Xintao Wu

CoRR, 2020

Transfer Heterogeneous Knowledge Among Peer-to-Peer Teammates: A Model Distillation Approach.

Zeyue Xue, Shuang Luo, Chao Wu, Pan Zhou, Kaigui Bian, Wei Du

CoRR, 2020

A Framework to Preserve User Privacy for Machine Learning as a Service.

Ben Niu, Likun Zhang, Yahong Chen, Ang Li, Wei Du, Jin Cao, Fenghua Li

Proceedings of the IEEE Global Communications Conference, 2020

AdvPL: Adversarial Personalized Learning.

Wei Du, Xintao Wu

Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020

2018

Privacy-Preserving Outsourcing of Large-Scale Nonlinear Programming to the Cloud.

Ang Li, Wei Du, Qinghua Li

Proceedings of the Security and Privacy in Communication Networks, 2018

PoliteCamera: Respecting Strangers' Privacy in Mobile Photographing.

Ang Li, Wei Du, Qinghua Li

Proceedings of the Security and Privacy in Communication Networks, 2018

Privacy-Preserving Multiparty Learning for Logistic Regression.

Wei Du, Ang Li, Qinghua Li

Proceedings of the Security and Privacy in Communication Networks, 2018

2017

Secure and efficient outsourcing of large-scale nonlinear programming.

Wei Du, Qinghua Li

Proceedings of the 2017 IEEE Conference on Communications and Network Security, 2017