Huang, Xiaolin

39 publications

ICML 2025 Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape Tao Li, Zhengbao He, Yujun Li, Yasheng Wang, Lifeng Shang, Xiaolin Huang

MLJ 2025 MUSO: Achieving Exact Machine Unlearning in Over-Parameterized Regimes Ruikai Yang, Mingzhen He, Zhenghao He, Youmei Qiu, Xiaolin Huang

AAAI 2025 ParseCaps: An Interpretable Parsing Capsule Network for Medical Image Diagnosis Xinyu Geng, Jiaming Wang, Xiaolin Huang, Fanglin Chen, Jun Xu

ICML 2025 Primphormer: Efficient Graph Transformers with Primal Representations Mingzhen He, Ruikai Yang, Hanling Tian, Youmei Qiu, Xiaolin Huang

ICLR 2025 Pursuing Feature Separation Based on Neural Collapse for Out-of-Distribution Detection Yingwen Wu, Ruiji Yu, Xinwen Cheng, Zhengbao He, Xiaolin Huang

ICLR 2025 Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks Hanling Tian, Yuhang Liu, Mingzhen He, Zhengbao He, Zhehao Huang, Ruikai Yang, Xiaolin Huang

ECML-PKDD 2025 Stimulating Catastrophic Forgetting in Class-Wise Unlearning via UAP Wenxing Zhou, Xinwen Cheng, Yingwen Wu, Ruikai Yang, Xiaolin Huang

NeurIPSW 2024 Flat-LoRA: Low-Rank Adaption over a Flat Loss Landscape Tao Li, Zhengbao He, Yujun Li, Yasheng Wang, Lifeng Shang, Xiaolin Huang

CVPR 2024 Friendly Sharpness-Aware Minimization Tao Li, Pan Zhou, Zhengbao He, Xinwen Cheng, Xiaolin Huang

NeurIPS 2024 Kernel PCA for Out-of-Distribution Detection Kun Fang, Qinghua Tao, Kexin Lv, Mingzhen He, Xiaolin Huang, Jie Yang

ECCV 2024 Learning Scalable Model Soup on a Single GPU: An Efficient Subspace Training Strategy Tao Li, Weisen Jiang, Fanghui Liu, Xiaolin Huang, James Kwok

TMLR 2024 Online Continual Learning via Logit Adjusted SoftMax Zhehao Huang, Tao Li, Chenhe Yuan, Yingwen Wu, Xiaolin Huang

CVPR 2024 OrthCaps: An Orthogonal CapsNet with Sparse Attention Routing and Pruning Xinyu Geng, Jiaming Wang, Jiawei Gong, Yuerong Xue, Jun Xu, Fanglin Chen, Xiaolin Huang

MLJ 2024 Random Fourier Features for Asymmetric Kernels Mingzhen He, Fan He, Fanghui Liu, Xiaolin Huang

TMLR 2024 Revisiting Random Weight Perturbation for Efficiently Improving Generalization Tao Li, Qinghua Tao, Weihao Yan, Yingwen Wu, Zehao Lei, Kun Fang, Mingzhen He, Xiaolin Huang

NeurIPSW 2024 Towards Natural Machine Unlearning Zhengbao He, Tao Li, Xinwen Cheng, Zhehao Huang, Xiaolin Huang

NeurIPS 2024 Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement Zhehao Huang, Xinwen Cheng, JingHao Zheng, Haoran Wang, Zhengbao He, Tao Li, Xiaolin Huang

ACML 2023 Better Loss Landscape Visualization for Deep Neural Networks with Trajectory Information Ruiqi Ding, Tao Li, Xiaolin Huang

NeurIPS 2023 Diffusion Representation for Asymmetric Kernels via Magnetic Transform Mingzhen He, Fan He, Ruikai Yang, Xiaolin Huang

CVPRW 2023 Investigating Catastrophic Overfitting in Fast Adversarial Training: A Self-Fitting Perspective Zhengbao He, Tao Li, Sizhe Chen, Xiaolin Huang

ICLR 2023 One-Pixel Shortcut: On the Learning Preference of Deep Neural Networks Shutong Wu, Sizhe Chen, Cihang Xie, Xiaolin Huang

NeurIPSW 2023 Revisiting Random Weight Perturbation for Efficiently Improving Generalization Tao Li, Weihao Yan, Qinghua Tao, Zehao Lei, Yingwen Wu, Kun Fang, Mingzhen He, Xiaolin Huang

ICLR 2023 Self-Ensemble Protection: Training Checkpoints Are Good Data Protectors Sizhe Chen, Geng Yuan, Xinwen Cheng, Yifan Gong, Minghai Qin, Yanzhi Wang, Xiaolin Huang

ICLR 2023 Trainable Weight Averaging: Efficient Training by Optimizing Historical Solutions Tao Li, Zhehao Huang, Qinghua Tao, Yingwen Wu, Xiaolin Huang

MLJ 2023 Weighted Neural Tangent Kernel: A Generalized and Improved Network-Induced Kernel Lei Tan, Shutong Wu, Wenxing Zhou, Xiaolin Huang

NeurIPS 2022 Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks Sizhe Chen, Zhehao Huang, Qinghua Tao, Yingwen Wu, Cihang Xie, Xiaolin Huang

ECCV 2022 PCR-CG: Point Cloud Registration via Deep Explicit Color and Geometry Yu Zhang, Junle Yu, Xiaolin Huang, Wenhui Zhou, Ji Hou

CVPR 2022 Subspace Adversarial Training Tao Li, Yingwen Wu, Sizhe Chen, Kun Fang, Xiaolin Huang

AISTATS 2021 Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures Fanghui Liu, Xiaolin Huang, Yingyi Chen, Johan Suykens

MLJ 2021 Analysis of Regularized Least-Squares in Reproducing Kernel Kreĭn Spaces Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens

ICCVW 2021 CDAda: A Curriculum Domain Adaptation for Nighttime Semantic Segmentation Qi Xu, Yinan Ma, Jing Wu, Chengnian Long, Xiaolin Huang

JMLR 2021 Generalization Properties of Hyper-RKHS and Its Applications Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A.K. Suykens

AAAI 2020 A Generalized Framework for Edge-Preserving and Structure-Preserving Image Smoothing Wei Liu, Pingping Zhang, Yinjie Lei, Xiaolin Huang, Jie Yang, Ian D. Reid

JMLR 2020 Learning Data-Adaptive Non-Parametric Kernels Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang, Li Li

AAAI 2020 Random Fourier Features via Fast Surrogate Leverage Weighted Sampling Fanghui Liu, Xiaolin Huang, Yudong Chen, Jie Yang, Johan A. K. Suykens

JMLR 2019 Sparse Kernel Regression with Coefficient-Based $\ell_q-$regularization Lei Shi, Xiaolin Huang, Yunlong Feng, Johan A.K. Suykens

AAAI 2018 Nonlinear Pairwise Layer and Its Training for Kernel Learning Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang, Li Li

JMLR 2015 Learning with the Maximum Correntropy Criterion Induced Losses for Regression Yunlong Feng, Xiaolin Huang, Lei Shi, Yuning Yang, Johan A.K. Suykens

JMLR 2014 Ramp Loss Linear Programming Support Vector Machine Xiaolin Huang, Lei Shi, Johan A.K. Suykens