Kun Fang

35 papers A* 3A 1B 2Journal 26Unranked 3
YearRankTypeTitle / Venue / Authors
2026 A* conf
DIFT: Protecting Contrastive Learning Against Data Poisoning Backdoor Attacks.
AAAI
Jiang Zhu, Yulin Jin, Qingqing Ye, Zhibiao Guo, Kun Fang, Ruochen Du, Yingnan Zhao, Haibo Hu
2026 J jnl
FIT: Defying Catastrophic Forgetting in Continual LLM Unlearning.
CoRR
Xiaoyu Xu, Minxin Du, Kun Fang, Zi Liang, Yaxin Xiao, Zhicong Huang, Cheng Hong, Qingqing Ye, Haibo Hu
2026 J jnl
MLOW: Interpretable Low-Rank Frequency Magnitude Decomposition of Multiple Effects for Time Series Forecasting.
CoRR
Runze Yang, Longbing Cao, Xiao-Ming Wu, Xin You, Kun Fang, Jianxun Li, Jie Yang
2026 J jnl
Machine Unlearning in Low-Dimensional Feature Subspace.
CoRR
Kun Fang, Qinghua Tao, Junxu Liu, Yaxin Xiao, Qingqing Ye, Jian Sun, Haibo Hu
2025 J jnl
Fourier Basis Mapping: A Time-Frequency Learning Framework for Time Series Forecasting.
CoRR
Runze Yang, Longbing Cao, Xin You, Kun Fang, Jianxun Li, Jie Yang
2025 J jnl
Kernel PCA for Out-of-Distribution Detection: Non-Linear Kernel Selections and Approximations.
CoRR
Kun Fang, Qinghua Tao, Mingzhen He, Kexin Lv, Runze Yang, Haibo Hu, Xiaolin Huang, Jie Yang, Longbing Cao
2025 J jnl
Multi-head ensemble of smoothed classifiers for certified robustness.
Neural Networks
Kun Fang, Qinghua Tao, Yingwen Wu, Tao Li, Xiaolin Huang, Jie Yang
2024 J jnl
Boosting certified robustness via an expectation-based similarity regularization.
Image Vis. Comput.
Jiawen Li, Kun Fang, Xiaolin Huang, Jie Yang
2024 J jnl
DDoS: Diffusion Distribution Similarity for Out-of-Distribution Detection.
CoRR
Kun Fang, Qinghua Tao, Zuopeng Yang, Xiaolin Huang, Jie Yang
2024 A* conf
Kernel PCA for Out-of-Distribution Detection.
NeurIPS
Kun Fang, Qinghua Tao, Kexin Lv, Mingzhen He, Xiaolin Huang, Jie Yang
2024 J jnl
Kernel PCA for Out-of-Distribution Detection.
CoRR
Kun Fang, Qinghua Tao, Kexin Lv, Mingzhen He, Xiaolin Huang, Jie Yang
2024 J jnl
Revisiting Deep Ensemble for Out-of-Distribution Detection: A Loss Landscape Perspective.
Int. J. Comput. Vis.
Kun Fang, Qinghua Tao, Xiaolin Huang, Jie Yang
2024 J jnl
Revisiting Random Weight Perturbation for Efficiently Improving Generalization.
CoRR
Tao Li, Qinghua Tao, Weihao Yan, Zehao Lei, Yingwen Wu, Kun Fang, Mingzhen He, Xiaolin Huang
2024 J jnl
Revisiting Random Weight Perturbation for Efficiently Improving Generalization.
Trans. Mach. Learn. Res.
Tao Li, Qinghua Tao, Weihao Yan, Yingwen Wu, Zehao Lei, Kun Fang, Mingzhen He, Xiaolin Huang
2024 J jnl
Towards robust neural networks via orthogonal diversity.
Pattern Recognit.
Kun Fang, Qinghua Tao, Yingwen Wu, Tao Li, Jia Cai, Feipeng Cai, Xiaolin Huang, Jie Yang
2023 J jnl
End-to-end kernel learning via generative random Fourier features.
Pattern Recognit.
Kun Fang, Fanghui Liu, Xiaolin Huang, Jie Yang
2023 J jnl
Improving adversarial robustness through a curriculum-guided reliable distillation.
Comput. Secur.
Jiawen Li, Kun Fang, Xiaolin Huang, Jie Yang
2023 J jnl
Improving the adversarial robustness of quantized neural networks via exploiting the feature diversity.
Pattern Recognit. Lett.
Tianshu Chu, Kun Fang, Jie Yang, Xiaolin Huang
2023 J jnl
Revisiting Deep Ensemble for Out-of-Distribution Detection: A Loss Landscape Perspective.
CoRR
Kun Fang, Qinghua Tao, Xiaolin Huang, Jie Yang
2023 J jnl
Unifying Gradients to Improve Real-World Robustness for Deep Networks.
ACM Trans. Intell. Syst. Technol.
Yingwen Wu, Sizhe Chen, Kun Fang, Xiaolin Huang
2022 A conf
CROON: Automatic Multi-LiDAR Calibration and Refinement Method in Road Scene.
IROS
Pengjin Wei, Guohang Yan, Yikang Li, Kun Fang, Xinyu Cai, Jie Yang, Wei Liu
2022 J jnl
CROON: Automatic Multi-LiDAR Calibration and Refinement Method in Road Scene.
CoRR
Pengjin Wei, Guohang Yan, Yikang Li, Kun Fang, Wei Liu, Xinyu Cai, Jie Yang
2022 J jnl
Efficient Generalization Improvement Guided by Random Weight Perturbation.
CoRR
Tao Li, Weihao Yan, Zehao Lei, Yingwen Wu, Kun Fang, Ming Yang, Xiaolin Huang
2022 — conf
Learnable Relation with Triplet Formulation for Semi-supervised Medical Image Classification.
DMBD (1)
Yiming Sun, Zhiqiang Xie, Kun Fang, Enmei Tu, Jie Yang
2022 — conf
Local-Global Semantic Fusion Single-shot Classification Method.
ICONIP (1)
Jianwei Cai, Kun Fang, Weihao Yu, Jie Yang, Yu Qiao
2022 J jnl
On Multi-head Ensemble of Smoothed Classifiers for Certified Robustness.
CoRR
Kun Fang, Qinghua Tao, Yingwen Wu, Tao Li, Xiaolin Huang, Jie Yang
2022 A* conf
Subspace Adversarial Training.
CVPR
Tao Li, Yingwen Wu, Sizhe Chen, Kun Fang, Xiaolin Huang
2022 J jnl
Unifying Gradients to Improve Real-world Robustness for Deep Networks.
CoRR
Yingwen Wu, Sizhe Chen, Kun Fang, Xiaolin Huang
2021 B conf
ADVMIX: Data Augmentation for Accurate Scene Text Spotting.
ICIP
Yizhang Huang, Kun Fang, Xiaolin Huang, Jie Yang
2021 — conf
Robust Deep Facial Attribute Prediction against Adversarial Attacks.
ICCAI
Kun Fang, Jie Yang
2021 J jnl
Subspace Adversarial Training.
CoRR
Tao Li, Yingwen Wu, Sizhe Chen, Kun Fang, Xiaolin Huang
2021 B conf
Towards Unbiased Random Features with Lower Variance For Stationary Indefinite Kernels.
IJCNN
Qin Luo, Kun Fang, Jie Yang, Xiaolin Huang
2021 J jnl
Towards Unbiased Random Features with Lower Variance For Stationary Indefinite Kernels.
CoRR
Qin Luo, Kun Fang, Jie Yang, Xiaolin Huang
2020 J jnl
End-to-end Kernel Learning via Generative Random Fourier Features.
CoRR
Kun Fang, Xiaolin Huang, Fanghui Liu, Jie Yang
2020 J jnl
Learn Robust Features via Orthogonal Multi-Path.
CoRR
Kun Fang, Yingwen Wu, Tao Li, Xiaolin Huang, Jie Yang