Secure and efficient outsourcing of large-scale nonlinear programming. - Wei Du 009; Qinghua Li (CNS, 2017)

Privacy-Preserving Multiparty Learning for Logistic Regression. - Wei Du 009; Ang Li 005; Qinghua Li (SecureComm (1), 2018)

PoliteCamera: Respecting Strangers' Privacy in Mobile Photographing. - Ang Li 005; Wei Du 009; Qinghua Li (SecureComm (1), 2018)

Privacy-Preserving Outsourcing of Large-Scale Nonlinear Programming to the Cloud. - Ang Li 005; Wei Du 009; Qinghua Li (SecureComm (1), 2018)

AdvPL: Adversarial Personalized Learning. - Wei Du 009; Xintao Wu (DSAA, 2020)

A Framework to Preserve User Privacy for Machine Learning as a Service. - Ben Niu 001; Likun Zhang; Yahong Chen; Ang Li 005; Wei Du 009; Jin Cao 001; Fenghua Li (GLOBECOM, 2020)

Transfer Heterogeneous Knowledge Among Peer-to-Peer Teammates: A Model Distillation Approach. - Zeyue Xue; Shuang Luo; Chao Wu; Pan Zhou 001; Kaigui Bian; Wei Du 009 (CoRR, 2020)

Removing Disparate Impact of Differentially Private Stochastic Gradient Descent on Model Accuracy. - Depeng Xu 001; Wei Du 009; Xintao Wu (CoRR, 2020)

Approximate to Be Great: Communication Efficient and Privacy-Preserving Large-Scale Distributed Deep Learning in Internet of Things. - Wei Du 009; Ang Li 005; Pan Zhou 001; Zichuan Xu; Xiumin Wang; Hao Jiang 010; Dapeng Oliver Wu (IEEE Internet Things J., 2020)

Fair and Robust Classification Under Sample Selection Bias. - Wei Du 009; Xintao Wu (CIKM, 2021)

Removing Disparate Impact on Model Accuracy in Differentially Private Stochastic Gradient Descent. - Depeng Xu 001; Wei Du 009; Xintao Wu (KDD, 2021)

Fairness-aware Agnostic Federated Learning. - Wei Du 009; Depeng Xu 001; Xintao Wu; Hanghang Tong (SDM, 2021)

Robust Fairness-aware Learning Under Sample Selection Bias. - Wei Du 009; Xintao Wu (CoRR, 2021)

Enhancing personalized modeling via weighted and adversarial learning. - Wei Du 009; Xintao Wu (Int. J. Data Sci. Anal., 2021)

Massive Maritime Path Planning: A Contextual Online Learning Approach. - Pan Zhou 001; Weiguang Zhao; Jianghui Li; Ang Li 005; Wei Du 009; Shiping Wen 001 (IEEE Trans. Cybern., 2021)

Robust Personalized Federated Learning under Demographic Fairness Heterogeneity. - Alycia N. Carey; Wei Du 009; Xintao Wu (IEEE Big Data, 2022)

Fair Regression under Sample Selection Bias. - Wei Du 009; Xintao Wu; Hanghang Tong (IEEE Big Data, 2022)

Defending Evasion Attacks via Adversarially Adaptive Training. - Minh-Hao Van; Wei Du 009; Xintao Wu; Feng Chen 001; Aidong Lu (IEEE Big Data, 2022)

Poisoning Attacks on Fair Machine Learning. - Minh-Hao Van; Wei Du 009; Xintao Wu; Aidong Lu (DASFAA (1), 2022)

PrivacyEye: A Privacy-Preserving and Computationally Efficient Deep Learning-Based Mobile Video Analytics System. - Wei Du 009; Ang Li 005; Pan Zhou 001; Ben Niu 001; Dapeng Wu 001 (IEEE Trans. Mob. Comput., 2022)

A Robust Classifier under Missing-Not-at-Random Sample Selection Bias. - Huy Mai; Wen Huang 003; Wei Du 009; Xintao Wu (IEEE Big Data, 2023)

3DHacker: Spectrum-based Decision Boundary Generation for Hard-label 3D Point Cloud Attack. - Yunbo Tao; Daizong Liu; Pan Zhou 001; Yulai Xie; Wei Du 009; Wei Hu 003 (ICCV, 2023)

Privacy-Preserving and Secure Cloud Computing: A Case of Large-Scale Nonlinear Programming. - Wei Du 009; Ang Li 005; Qinghua Li; Pan Zhou 001 (IEEE Trans. Cloud Comput., 2023)