Sub-Architecture Ensemble Pruning in Neural Architecture Search. - Yijun Bian; Qingquan Song; Mengnan Du; Jun Yao; Huanhuan Chen; Xia Hu 001 (CoRR, 2019)

Ensemble Pruning Based on Objection Maximization With a General Distributed Framework. - Yijun Bian; Yijun Wang 002; Yaqiang Yao; Huanhuan Chen (IEEE Trans. Neural Networks Learn. Syst., 2020)

Adversarial Patch Attacks and Defences in Vision-Based Tasks: A Survey. - Abhijith Sharma; Yijun Bian; Phil Munz; Apurva Narayan (CoRR, 2022)

When Does Diversity Help Generalization in Classification Ensembles? - Yijun Bian; Huanhuan Chen (IEEE Trans. Cybern., 2022)

Subarchitecture Ensemble Pruning in Neural Architecture Search. - Yijun Bian; Qingquan Song; Mengnan Du; Jun Yao; Huanhuan Chen; Xia Hu 001 (IEEE Trans. Neural Networks Learn. Syst., 2022)

Vulnerability of CNNs against Multi-Patch Attacks. - Abhijith Sharma; Yijun Bian; Vatsal Nanda; Phil Munz; Apurva Narayan (SAT-CPS@CODASPY, 2023)

Increasing Fairness in Compromise on Accuracy via Weighted Vote with Learning Guarantees. - Yijun Bian; Kun Zhang 001 (CoRR, 2023)

Advancing Graph Neural Networks with HL-HGAT: A Hodge-Laplacian and Attention Mechanism Approach for Heterogeneous Graph-Structured Data. - Jinghan Huang 002; Qiufeng Chen; Yijun Bian; Pengli Zhu; Nanguang Chen; Moo K. Chung; Anqi Qiu (CoRR, 2024)

Does Machine Bring in Extra Bias in Learning? Approximating Fairness in Models Promptly. - Yijun Bian; Yujie Luo (CoRR, 2024)

Approximating Discrimination Within Models When Faced With Several Non-Binary Sensitive Attributes. - Yijun Bian; Yujie Luo; Ping Xu (CoRR, 2024)

Refining Counterfactual Explanations With Joint-Distribution-Informed Shapley Towards Actionable Minimality. - Lei You 002; Yijun Bian; Lele Cao (CoRR, 2024)

Orthogonal Mixed-Effects Modeling for High-Dimensional Longitudinal Data: An Unsupervised Learning Approach. - Ming Chen; Yijun Bian; Nanguang Chen; Anqi Qiu (IEEE Trans. Medical Imaging, 2025)

Towards Trustworthy Federated Learning. - Alina Basharat; Yijun Bian; Ping Xu; Zhi Tian (CoRR, 2025)

FairSHAP: Preprocessing for Fairness Through Attribution-Based Data Augmentation. - Lin Zhu; Yijun Bian; Lei You 002 (CoRR, 2025)

Fairness Research For Machine Learning Should Integrate Societal Considerations. - Yijun Bian; Lei You 002 (CoRR, 2025)