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Yijun Bian
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2020 – today
- 2024
- [i8]Jinghan Huang, Qiufeng Chen, Yijun Bian, Pengli Zhu, Nanguang Chen, Moo K. Chung, Anqi Qiu:
Advancing Graph Neural Networks with HL-HGAT: A Hodge-Laplacian and Attention Mechanism Approach for Heterogeneous Graph-Structured Data. CoRR abs/2403.06687 (2024) - [i7]Yijun Bian, Yujie Luo:
Does Machine Bring in Extra Bias in Learning? Approximating Fairness in Models Promptly. CoRR abs/2405.09251 (2024) - [i6]Yijun Bian, Yujie Luo, Ping Xu:
Approximating Discrimination Within Models When Faced With Several Non-Binary Sensitive Attributes. CoRR abs/2408.06099 (2024) - 2023
- [c1]Abhijith Sharma, Yijun Bian, Vatsal Nanda, Phil Munz, Apurva Narayan:
Vulnerability of CNNs against Multi-Patch Attacks. SAT-CPS@CODASPY 2023: 23-32 - [i5]Yijun Bian, Kun Zhang:
Increasing Fairness in Compromise on Accuracy via Weighted Vote with Learning Guarantees. CoRR abs/2301.10813 (2023) - 2022
- [j3]Yijun Bian, Huanhuan Chen:
When Does Diversity Help Generalization in Classification Ensembles? IEEE Trans. Cybern. 52(9): 9059-9075 (2022) - [j2]Yijun Bian, Qingquan Song, Mengnan Du, Jun Yao, Huanhuan Chen, Xia Hu:
Subarchitecture Ensemble Pruning in Neural Architecture Search. IEEE Trans. Neural Networks Learn. Syst. 33(12): 7928-7936 (2022) - [i4]Abhijith Sharma, Yijun Bian, Phil Munz, Apurva Narayan:
Adversarial Patch Attacks and Defences in Vision-Based Tasks: A Survey. CoRR abs/2206.08304 (2022) - 2020
- [j1]Yijun Bian, Yijun Wang, Yaqiang Yao, Huanhuan Chen:
Ensemble Pruning Based on Objection Maximization With a General Distributed Framework. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3766-3774 (2020)
2010 – 2019
- 2019
- [i3]Yijun Bian, Qingquan Song, Mengnan Du, Jun Yao, Huanhuan Chen, Xia Hu:
Sub-Architecture Ensemble Pruning in Neural Architecture Search. CoRR abs/1910.00370 (2019) - [i2]Yijun Bian, Huanhuan Chen:
When does Diversity Help Generalization in Classification Ensembles? CoRR abs/1910.13631 (2019) - 2018
- [i1]Yijun Bian, Yijun Wang, Yaqiang Yao, Huanhuan Chen:
Ensemble Pruning based on Objection Maximization with a General Distributed Framework. CoRR abs/1806.04899 (2018)
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