Jun Yu

Winning Prize Comes from Losing Tickets: Improve Invariant Learning by Exploring Variant Parameters for Out-of-Distribution Generalization

Zhuo Huang, Li Shen, Chen Gong, 2023, International Journal of Computer Vision.

Neural auto-designer for enhanced quantum kernels

Peng Mi, Yuxuan Du, Jun Yu, 2024, ICLR.

FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised Learning

Zhuo Huang, Li Shen, Tongliang Liu, 2023, NeurIPS.

Combating Noisy Labels with Sample Selection by Mining High-Discrepancy Examples

Xiaobo Xia, Yibing Zhan, Tongliang Liu, 2023, 2023 IEEE/CVF International Conference on Computer Vision (ICCV).

Mitigating Label Noise on Graph via Topological Sample Selection

Xiaobo Xia, Jiangchao Yao, Tongliang Liu, 2024, ArXiv.

On the Onset of Robust Overfitting in Adversarial Training

Chaojian Yu, Tongliang Liu, Jun Yu, 2023, ArXiv.

Subclass-Dominant Label Noise: A Counterexample for the Success of Early Stopping

Erkun Yang, Ying-Long Bai, Tongliang Liu, 2023, NeurIPS.

Tackling Noisy Labels With Network Parameter Additive Decomposition

Xiaobo Xia, Tongliang Liu, Bo Han, 2024, IEEE Transactions on Pattern Analysis and Machine Intelligence.