Feng, Lei

85 publications

ICML 2025 A Closer Look at Backdoor Attacks on CLIP Shuo He, Zhifang Zhang, Feng Liu, Roy Ka-Wei Lee, Bo An, Lei Feng

ICLR 2025 Attribute-Based Visual Reprogramming for Vision-Language Models Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu

NeurIPS 2025 Defending Multimodal Backdoored Models by Repulsive Visual Prompt Tuning Zhifang Zhang, Shuo He, Haobo Wang, Bingquan Shen, Lei Feng

TMLR 2025 Does Confidence Calibration Improve Conformal Prediction? HuaJun Xi, Jianguo Huang, Kangdao Liu, Lei Feng, Hongxin Wei

ICLR 2025 Endowing Visual Reprogramming with Adversarial Robustness Shengjie Zhou, Xin Cheng, Haiyang Xu, Ming Yan, Tao Xiang, Feng Liu, Lei Feng

NeurIPS 2025 Enhancing Sample Selection Against Label Noise by Cutting Mislabeled Easy Examples Suqin Yuan, Lei Feng, Bo Han, Tongliang Liu

ICML 2025 Enhancing the Influence of Labels on Unlabeled Nodes in Graph Convolutional Networks Jincheng Huang, Yujie Mo, Xiaoshuang Shi, Lei Feng, Xiaofeng Zhu

NeurIPS 2025 Establishing Linear Surrogate Regret Bounds for Convex Smooth Losses via Convolutional Fenchel–Young Losses Yuzhou Cao, Han Bao, Lei Feng, Bo An

ICML 2025 Exploiting Presentative Feature Distributions for Parameter-Efficient Continual Learning of Large Language Models Xin Cheng, Jiabo Ye, Haiyang Xu, Ming Yan, Ji Zhang, Feng Liu, Fei Huang, Lei Feng

TMLR 2025 Exploring Weak-to-Strong Generalization for CLIP-Based Classification Jinhao Li, Sarah Monazam Erfani, Lei Feng, James Bailey, Feng Liu

AAAI 2025 Improving Generalization of Deep Neural Networks by Optimum Shifting Yuyan Zhou, Ye Li, Lei Feng, Sheng-Jun Huang

AAAI 2025 Influence-Based Fair Selection for Sample-Discriminative Backdoor Attack Qi Wei, Shuo He, Jiahan Zhang, Lei Feng, Bo An

ICLR 2025 Instance-Dependent Early Stopping Suqin Yuan, Runqi Lin, Lei Feng, Bo Han, Tongliang Liu

IJCAI 2025 Prototype-Based Optimal Transport for Out-of-Distribution Detection Ao Ke, Wenlong Chen, Chuanwen Feng, Yukun Cao, Xike Xie, S. Kevin Zhou, Lei Feng

ICML 2025 Representation Surgery in Model Merging with Probabilistic Modeling Qi Wei, Shuo He, Enneng Yang, Tingcong Liu, Haobo Wang, Lei Feng, Bo An

ICML 2025 Rethinking Chain-of-Thought from the Perspective of Self-Training Zongqian Wu, Baoduo Xu, Ruochen Cui, Mengmeng Zhan, Xiaofeng Zhu, Lei Feng

ICML 2025 Test-Time Multimodal Backdoor Detection by Contrastive Prompting Yuwei Niu, Shuo He, Qi Wei, Zongyu Wu, Feng Liu, Lei Feng

IJCAI 2025 Towards Robust Incremental Learning Under Ambiguous Supervision Rui Wang, Mingxuan Xia, Haobo Wang, Lei Feng, Junbo Zhao, Gang Chen, Chang Yao

ICML 2025 Understanding Model Reprogramming for CLIP via Decoupling Visual Prompts Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu

ICML 2024 A General Framework for Learning from Weak Supervision Hao Chen, Jindong Wang, Lei Feng, Xiang Li, Yidong Wang, Xing Xie, Masashi Sugiyama, Rita Singh, Bhiksha Raj

NeurIPS 2024 Bayesian-Guided Label Mapping for Visual Reprogramming Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu

ICLR 2024 Candidate Label Set Pruning: A Data-Centric Perspective for Deep Partial-Label Learning Shuo He, Chaojie Wang, Guowu Yang, Lei Feng

ICML 2024 Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data Jiahan Zhang, Qi Wei, Feng Liu, Lei Feng

AISTATS 2024 Consistent Hierarchical Classification with a Generalized Metric Yuzhou Cao, Lei Feng, Bo An

ICLR 2024 Consistent Multi-Class Classification from Multiple Unlabeled Datasets Zixi Wei, Senlin Shu, Yuzhou Cao, Hongxin Wei, Bo An, Lei Feng

MLJ 2024 Correction: Learning Sample-Aware Threshold for Semi-Supervised Learning Qi Wei, Lei Feng, Haoliang Sun, Ren Wang, Rundong He, Yilong Yin

CVPR 2024 CroSel: Cross Selection of Confident Pseudo Labels for Partial-Label Learning Shiyu Tian, Hongxin Wei, Yiqun Wang, Lei Feng

ICLR 2024 Early Stopping Against Label Noise Without Validation Data Suqin Yuan, Lei Feng, Tongliang Liu

MLJ 2024 Exploiting Counter-Examples for Active Learning with Partial Labels Fei Zhang, Yunjie Ye, Lei Feng, Zhongwen Rao, Jieming Zhu, Marcus Kalander, Chen Gong, Jianye Hao, Bo Han

ICML 2024 Exploiting Human-AI Dependence for Learning to Defer Zixi Wei, Yuzhou Cao, Lei Feng

CVPR 2024 Investigating and Mitigating the Side Effects of Noisy Views for Self-Supervised Clustering Algorithms in Practical Multi-View Scenarios Jie Xu, Yazhou Ren, Xiaolong Wang, Lei Feng, Zheng Zhang, Gang Niu, Xiaofeng Zhu

MLJ 2024 Learning Sample-Aware Threshold for Semi-Supervised Learning Qi Wei, Lei Feng, Haoliang Sun, Ren Wang, Rundong He, Yilong Yin

ICML 2024 Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss Zhenlong Liu, Lei Feng, Huiping Zhuang, Xiaofeng Cao, Hongxin Wei

AISTATS 2024 Mitigating Underfitting in Learning to Defer with Consistent Losses Shuqi Liu, Yuzhou Cao, Qiaozhen Zhang, Lei Feng, Bo An

ICLR 2024 On the Vulnerability of Adversarially Trained Models Against Two-Faced Attacks Shengjie Zhou, Lue Tao, Yuzhou Cao, Tao Xiang, Bo An, Lei Feng

MLJ 2024 Online Binary Classification from Similar and Dissimilar Data Senlin Shu, Haobo Wang, Zhuowei Wang, Bo Han, Tao Xiang, Bo An, Lei Feng

ICML 2024 Positive and Unlabeled Learning with Controlled Probability Boundary Fence Changchun Li, Yuanchao Dai, Lei Feng, Ximing Li, Bing Wang, Jihong Ouyang

CVPR 2024 Positive-Unlabeled Learning by Latent Group-Aware Meta Disambiguation Lin Long, Haobo Wang, Zhijie Jiang, Lei Feng, Chang Yao, Gang Chen, Junbo Zhao

AAAI 2024 Robust Node Classification on Graph Data with Graph and Label Noise Yonghua Zhu, Lei Feng, Zhenyun Deng, Yang Chen, Robert Amor, Michael Witbrock

ICML 2024 Sample-Specific Masks for Visual Reprogramming-Based Prompting Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu

CVPR 2024 Targeted Representation Alignment for Open-World Semi-Supervised Learning Ruixuan Xiao, Lei Feng, Kai Tang, Junbo Zhao, Yixuan Li, Gang Chen, Haobo Wang

ICML 2024 Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models Jinhao Li, Haopeng Li, Sarah Monazam Erfani, Lei Feng, James Bailey, Feng Liu

AAAI 2023 A Generalized Unbiased Risk Estimator for Learning with Augmented Classes Senlin Shu, Shuo He, Haobo Wang, Hongxin Wei, Tao Xiang, Lei Feng

ICML 2023 A Universal Unbiased Method for Classification from Aggregate Observations Zixi Wei, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Xiaofeng Zhu, Heng Tao Shen

NeurIPS 2023 ALIM: Adjusting Label Importance Mechanism for Noisy Partial Label Learning Mingyu Xu, Zheng Lian, Lei Feng, Bin Liu, Jianhua Tao

NeurIPS 2023 Binary Classification with Confidence Difference Wei Wang, Lei Feng, Yuchen Jiang, Gang Niu, Min-Ling Zhang, Masashi Sugiyama

ICCV 2023 Candidate-Aware Selective Disambiguation Based on Normalized Entropy for Instance-Dependent Partial-Label Learning Shuo He, Guowu Yang, Lei Feng

AISTATS 2023 Consistent Complementary-Label Learning via Order-Preserving Losses Shuqi Liu, Yuzhou Cao, Qiaozhen Zhang, Lei Feng, Bo An

CVPR 2023 Fine-Grained Classification with Noisy Labels Qi Wei, Lei Feng, Haoliang Sun, Ren Wang, Chenhui Guo, Yilong Yin

NeurIPS 2023 In Defense of SoftMax Parametrization for Calibrated and Consistent Learning to Defer Yuzhou Cao, Hussein Mozannar, Lei Feng, Hongxin Wei, Bo An

ICCV 2023 Late Stopping: Avoiding Confidently Learning from Mislabeled Examples Suqin Yuan, Lei Feng, Tongliang Liu

ICML 2023 Mitigating Memorization of Noisy Labels by Clipping the Model Prediction Hongxin Wei, Huiping Zhuang, Renchunzi Xie, Lei Feng, Gang Niu, Bo An, Yixuan Li

ICCV 2023 Multi-Label Knowledge Distillation Penghui Yang, Ming-Kun Xie, Chen-Chen Zong, Lei Feng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang

NeurIPS 2023 On the Importance of Feature Separability in Predicting Out-of-Distribution Error Renchunzi Xie, Hongxin Wei, Lei Feng, Yuzhou Cao, Bo An

AAAI 2023 Partial-Label Regression Xin Cheng, Deng-Bao Wang, Lei Feng, Min-Ling Zhang, Bo An

IJCAI 2023 ProMix: Combating Label Noise via Maximizing Clean Sample Utility Ruixuan Xiao, Yiwen Dong, Haobo Wang, Lei Feng, Runze Wu, Gang Chen, Junbo Zhao

NeurIPS 2023 Regression with Cost-Based Rejection Xin Cheng, Yuzhou Cao, Haobo Wang, Hongxin Wei, Bo An, Lei Feng

NeurIPS 2023 SPA: A Graph Spectral Alignment Perspective for Domain Adaptation Zhiqing Xiao, Haobo Wang, Ying Jin, Lei Feng, Gang Chen, Fei Huang, Junbo Zhao

ICML 2023 Weakly Supervised Regression with Interval Targets Xin Cheng, Yuzhou Cao, Ximing Li, Bo An, Lei Feng

NeurIPS 2022 Can Adversarial Training Be Manipulated by Non-Robust Features? Lue Tao, Lei Feng, Hongxin Wei, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen

ICLR 2022 Exploiting Class Activation Value for Partial-Label Learning Fei Zhang, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Tao Qin, Masashi Sugiyama

AAAI 2022 GearNet: Stepwise Dual Learning for Weakly Supervised Domain Adaptation Renchunzi Xie, Hongxin Wei, Lei Feng, Bo An

NeurIPS 2022 Generalizing Consistent Multi-Class Classification with Rejection to Be Compatible with Arbitrary Losses Yuzhou Cao, Tianchi Cai, Lei Feng, Lihong Gu, Jinjie Gu, Bo An, Gang Niu, Masashi Sugiyama

ICML 2022 Mitigating Neural Network Overconfidence with Logit Normalization Hongxin Wei, Renchunzi Xie, Hao Cheng, Lei Feng, Bo An, Yixuan Li

ICML 2022 Open-Sampling: Exploring Out-of-Distribution Data for Re-Balancing Long-Tailed Datasets Hongxin Wei, Lue Tao, Renchunzi Xie, Lei Feng, Bo An

ICLR 2022 PiCO: Contrastive Label Disambiguation for Partial Label Learning Haobo Wang, Ruixuan Xiao, Yixuan Li, Lei Feng, Gang Niu, Gang Chen, Junbo Zhao

TMLR 2022 SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning Zhuowei Wang, Jing Jiang, Bo Han, Lei Feng, Bo An, Gang Niu, Guodong Long

NeurIPS 2022 SoLar: Sinkhorn Label Refinery for Imbalanced Partial-Label Learning Haobo Wang, Mingxuan Xia, Yixuan Li, Yuren Mao, Lei Feng, Gang Chen, Junbo Zhao

ICLR 2022 Who Is Your Right Mixup Partner in Positive and Unlabeled Learning Changchun Li, Ximing Li, Lei Feng, Jihong Ouyang

AAAI 2022 With False Friends like These, Who Can Notice Mistakes? Lue Tao, Lei Feng, Jinfeng Yi, Songcan Chen

ICCV 2021 Attention Is Not Enough: Mitigating the Distribution Discrepancy in Asynchronous Multimodal Sequence Fusion Tao Liang, Guosheng Lin, Lei Feng, Yan Zhang, Fengmao Lv

NeurIPS 2021 Better Safe than Sorry: Preventing Delusive Adversaries with Adversarial Training Lue Tao, Lei Feng, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen

IJCAI 2021 Learning from Complementary Labels via Partial-Output Consistency Regularization Deng-Bao Wang, Lei Feng, Min-Ling Zhang

ICML 2021 Learning from Similarity-Confidence Data Yuzhou Cao, Lei Feng, Yitian Xu, Bo An, Gang Niu, Masashi Sugiyama

ICML 2021 Pointwise Binary Classification with Pairwise Confidence Comparisons Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama

NeurIPS 2021 Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence Deng-Bao Wang, Lei Feng, Min-Ling Zhang

IJCAI 2020 Can Cross Entropy Loss Be Robust to Label Noise? Lei Feng, Senlin Shu, Zhuoyi Lin, Fengmao Lv, Li Li, Bo An

IJCAI 2020 Discovering Latent Class Labels for Multi-Label Learning Jun Huang, Linchuan Xu, Jing Wang, Lei Feng, Kenji Yamanishi

ICML 2020 Learning with Multiple Complementary Labels Lei Feng, Takuo Kaneko, Bo Han, Gang Niu, Bo An, Masashi Sugiyama

ICML 2020 Progressive Identification of True Labels for Partial-Label Learning Jiaqi Lv, Miao Xu, Lei Feng, Gang Niu, Xin Geng, Masashi Sugiyama

NeurIPS 2020 Provably Consistent Partial-Label Learning Lei Feng, Jiaqi Lv, Bo Han, Miao Xu, Gang Niu, Xin Geng, Bo An, Masashi Sugiyama

AAAI 2019 Collaboration Based Multi-Label Learning Lei Feng, Bo An, Shuo He

IJCAI 2019 Partial Label Learning by Semantic Difference Maximization Lei Feng, Bo An

AAAI 2019 Partial Label Learning with Self-Guided Retraining Lei Feng, Bo An

IJCAI 2018 Leveraging Latent Label Distributions for Partial Label Learning Lei Feng, Bo An