Wei Du

Publication Activity (10 Years)

Years Active: 2018-2023
Publications (10 Years): 27

Top Topics

Sample Selection Bias

Differentially Private

Nonlinear Programming

Top Venues

Publications

Huy Mai, Wen Huang, Wei Du, Xintao Wu
A Robust Classifier under Missing-Not-at-Random Sample Selection Bias. BigData (2023)
Huy Mai, Wen Huang, Wei Du, Xintao Wu
A Robust Classifier Under Missing-Not-At-Random Sample Selection Bias. CoRR (2023)
Wei Du, Ang Li, Qinghua Li, Pan Zhou
Privacy-Preserving and Secure Cloud Computing: A Case of Large-Scale Nonlinear Programming. IEEE Trans. Cloud Comput. 11 (1) (2023)
Wei Du, Xintao Wu, Hanghang Tong
Fair Regression under Sample Selection Bias. Big Data (2022)
Wei Du, Ang Li, Pan Zhou, Ben Niu, Dapeng Wu
PrivacyEye: A Privacy-Preserving and Computationally Efficient Deep Learning-Based Mobile Video Analytics System. IEEE Trans. Mob. Comput. 21 (9) (2022)
Minh-Hao Van, Wei Du, Xintao Wu, Aidong Lu
Poisoning Attacks on Fair Machine Learning. DASFAA (1) (2022)
Minh-Hao Van, Wei Du, Xintao Wu, Feng Chen, Aidong Lu
Defending Evasion Attacks via Adversarially Adaptive Training. Big Data (2022)
Alycia N. Carey, Wei Du, Xintao Wu
Robust Personalized Federated Learning under Demographic Fairness Heterogeneity. Big Data (2022)
Wei Du, Xintao Wu
Enhancing personalized modeling via weighted and adversarial learning. Int. J. Data Sci. Anal. 12 (1) (2021)
Minh-Hao Van, Wei Du, Xintao Wu, Aidong Lu
Poisoning Attacks on Fair Machine Learning. CoRR (2021)
Wei Du, Xintao Wu, Hanghang Tong
Fair Regression under Sample Selection Bias. CoRR (2021)
Wei Du, Depeng Xu, Xintao Wu, Hanghang Tong
Fairness-aware Agnostic Federated Learning. SDM (2021)
Depeng Xu, Wei Du, Xintao Wu
Removing Disparate Impact on Model Accuracy in Differentially Private Stochastic Gradient Descent. KDD (2021)
Wei Du, Xintao Wu
Fair and Robust Classification Under Sample Selection Bias. CIKM (2021)
Pan Zhou, Weiguang Zhao, Jianghui Li, Ang Li, Wei Du, Shiping Wen
Massive Maritime Path Planning: A Contextual Online Learning Approach. IEEE Trans. Cybern. 51 (12) (2021)
Wei Du, Xintao Wu
Robust Fairness-aware Learning Under Sample Selection Bias. CoRR (2021)
Wei Du, Ang Li, Pan Zhou, Zichuan Xu, Xiumin Wang, Hao Jiang, Dapeng Oliver Wu
Approximate to Be Great: Communication Efficient and Privacy-Preserving Large-Scale Distributed Deep Learning in Internet of Things. IEEE Internet Things J. 7 (12) (2020)
Ang Li, Wei Du, Qinghua Li
PoliteCamera: Respecting Strangers' Privacy in Mobile Photographing. CoRR (2020)
Ben Niu, Likun Zhang, Yahong Chen, Ang Li, Wei Du, Jin Cao, Fenghua Li
A Framework to Preserve User Privacy for Machine Learning as a Service. GLOBECOM (2020)
Wei Du, Xintao Wu
AdvPL: Adversarial Personalized Learning. DSAA (2020)
Depeng Xu, Wei Du, Xintao Wu
Removing Disparate Impact of Differentially Private Stochastic Gradient Descent on Model Accuracy. CoRR (2020)
Wei Du, Depeng Xu, Xintao Wu, Hanghang Tong
Fairness-aware Agnostic Federated Learning. CoRR (2020)
Ang Li, Wei Du, Qinghua Li
PoliteCamera: Respecting Strangers' Privacy in Mobile Photographing. SecureComm (1) (2018)
Ang Li, Wei Du, Qinghua Li
Privacy-Preserving Outsourcing of Large-Scale Nonlinear Programming to the Cloud. CoRR (2018)
Wei Du, Ang Li, Qinghua Li
Privacy-Preserving Multiparty Learning For Logistic Regression. CoRR (2018)
Wei Du, Ang Li, Qinghua Li
Privacy-Preserving Multiparty Learning for Logistic Regression. SecureComm (1) (2018)
Ang Li, Wei Du, Qinghua Li
Privacy-Preserving Outsourcing of Large-Scale Nonlinear Programming to the Cloud. SecureComm (1) (2018)