Wei Du

Orcid: 0000-0002-3371-8305

Affiliations:
  • University of Arkansas, Department of Computer Science and Computer Engineering, Fayetteville, AR, USA


According to our database1, Wei Du authored at least 23 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2023
Privacy-Preserving and Secure Cloud Computing: A Case of Large-Scale Nonlinear Programming.
IEEE Trans. Cloud Comput., 2023

3DHacker: Spectrum-based Decision Boundary Generation for Hard-label 3D Point Cloud Attack.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

A Robust Classifier under Missing-Not-at-Random Sample Selection Bias.
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.
IEEE Trans. Mob. Comput., 2022

Poisoning Attacks on Fair Machine Learning.
Proceedings of the Database Systems for Advanced Applications, 2022

Defending Evasion Attacks via Adversarially Adaptive Training.
Proceedings of the IEEE International Conference on Big Data, 2022

Fair Regression under Sample Selection Bias.
Proceedings of the IEEE International Conference on Big Data, 2022

Robust Personalized Federated Learning under Demographic Fairness Heterogeneity.
Proceedings of the IEEE International Conference on Big Data, 2022

2021
Massive Maritime Path Planning: A Contextual Online Learning Approach.
IEEE Trans. Cybern., 2021

Enhancing personalized modeling via weighted and adversarial learning.
Int. J. Data Sci. Anal., 2021

Robust Fairness-aware Learning Under Sample Selection Bias.
CoRR, 2021

Fairness-aware Agnostic Federated Learning.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Removing Disparate Impact on Model Accuracy in Differentially Private Stochastic Gradient Descent.
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.
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.
IEEE Internet Things J., 2020

Removing Disparate Impact of Differentially Private Stochastic Gradient Descent on Model Accuracy.
CoRR, 2020

Transfer Heterogeneous Knowledge Among Peer-to-Peer Teammates: A Model Distillation Approach.
CoRR, 2020

A Framework to Preserve User Privacy for Machine Learning as a Service.
Proceedings of the IEEE Global Communications Conference, 2020

AdvPL: Adversarial Personalized Learning.
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.
Proceedings of the Security and Privacy in Communication Networks, 2018

PoliteCamera: Respecting Strangers' Privacy in Mobile Photographing.
Proceedings of the Security and Privacy in Communication Networks, 2018

Privacy-Preserving Multiparty Learning for Logistic Regression.
Proceedings of the Security and Privacy in Communication Networks, 2018

2017
Secure and efficient outsourcing of large-scale nonlinear programming.
Proceedings of the 2017 IEEE Conference on Communications and Network Security, 2017


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