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ORCIDLei Feng 0006
Person information
- affiliation: Southeast University, School of Computer Science and Engineering, Nanjing, China
- affiliation (2024): Singapore University of Technology and Design, Singapore
- affiliation (2023): Nanyang Technological University, Singapore
- affiliation (2021 - 2023): Chongqing University, China
- affiliation (PhD 2020): Nanyang Technological University, Singapore
Other persons with the same name
- Lei Feng — disambiguation page
- Lei Feng 0001
![[0000-0003-3494-5590]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-3494-5590")
— Beijing University of Posts and Telecommunications, State Key Laboratory of Networking and Switching Technology, China - Lei Feng 0002 — KTH Royal Institute of Technology, Stockholm, Sweden (and 1 more)
- Lei Feng 0003 — Jinling Institute of Technology, School of Computer Engineering, Nanjing, China (and 1 more)
- Lei Feng 0004 — University of Maryland, College Park, MD, USA
- Lei Feng 0005 — Capital Medical University, Mood Disorders Center, Beijing, China (and 1 more)
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2020 – today
- 2025
[j23]Beibei Li, Yiyuan Zheng, Beihong Jin, Tao Xiang, Haobo Wang, Lei Feng:
AsyCo: an asymmetric dual-task co-training model for partial-label learning. Sci. China Inf. Sci. 68(5) (2025)- [j22]Haoliang Sun, Qi Wei, Lei Feng, Yupeng Hu, Fan Liu, Hehe Fan, Yilong Yin:
Variational Rectification Inference for Learning with Noisy Labels. Int. J. Comput. Vis. 133(2): 652-671 (2025) - [j21]Haoliang Sun, Qi Wei, Lei Feng, Yupeng Hu, Fan Liu, Hehe Fan, Yilong Yin:
Correction: Variational Rectification Inference for Learning with Noisy Labels. Int. J. Comput. Vis. 133(3): 1434 (2025) - [j20]Jinhao Li, Sarah Monazam Erfani, Lei Feng, James Bailey, Feng Liu:
Exploring Weak-to-Strong Generalization for CLIP-based Classification. Trans. Mach. Learn. Res. 2025 (2025) - [j19]Huajun Xi, Jianguo Huang, Kangdao Liu, Lei Feng, Hongxin Wei:
Does confidence calibration improve conformal prediction? Trans. Mach. Learn. Res. 2025 (2025) - [c75]Yuyan Zhou, Ye Li, Lei Feng, Sheng-Jun Huang:
Improving Generalization of Deep Neural Networks by Optimum Shifting. AAAI 2025: 10870-10878 - [c74]Qi Wei, Shuo He, Jiahan Zhang, Lei Feng, Bo An:
Influence-Based Fair Selection for Sample-Discriminative Backdoor Attack. AAAI 2025: 21474-21481 - [c73]Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu:
Attribute-based Visual Reprogramming for Vision-Language Models. ICLR 2025 - [c72]Suqin Yuan, Runqi Lin, Lei Feng, Bo Han, Tongliang Liu:
Instance-dependent Early Stopping. ICLR 2025 - [c71]Shengjie Zhou, Xin Cheng, Haiyang Xu, Ming Yan, Tao Xiang, Feng Liu, Lei Feng:
Endowing Visual Reprogramming with Adversarial Robustness. ICLR 2025 - [c70]Rui Wang, Mingxuan Xia, Haobo Wang, Lei Feng, Junbo Zhao, Gang Chen, Chang Yao:
Towards Robust Incremental Learning Under Ambiguous Supervision. IJCAI 2025: 6397-6405 - [i74]Rui Wang, Mingxuan Xia, Chang Yao, Lei Feng, Junbo Zhao, Gang Chen, Haobo Wang:
Towards Robust Incremental Learning under Ambiguous Supervision. CoRR abs/2501.13584 (2025) - [i73]Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu:
Attribute-based Visual Reprogramming for Image Classification with CLIP. CoRR abs/2501.13982 (2025) - [i72]Suqin Yuan, Runqi Lin, Lei Feng, Bo Han, Tongliang Liu:
Instance-dependent Early Stopping. CoRR abs/2502.07547 (2025) - [i71]Suqin Yuan, Lei Feng, Tongliang Liu:
Early Stopping Against Label Noise Without Validation Data. CoRR abs/2502.07551 (2025) - [i70]Suqin Yuan, Lei Feng, Bo Han, Tongliang Liu:
Enhancing Sample Selection by Cutting Mislabeled Easy Examples. CoRR abs/2502.08227 (2025) - [i69]Zongqian Wu, Tianyu Li, Baoduo Xu, Jiaying Yang, Mengmeng Zhan, Xiaofeng Zhu, Lei Feng:
Is Depth All You Need? An Exploration of Iterative Reasoning in LLMs. CoRR abs/2502.10858 (2025) - [i68]Yuzhou Cao, Han Bao, Lei Feng, Bo An:
Establishing Linear Surrogate Regret Bounds for Convex Smooth Losses via Convolutional Fenchel-Young Losses. CoRR abs/2505.09432 (2025) - [i67]Jincheng Huang, Jie Xu, Xiaoshuang Shi, Ping Hu, Lei Feng, Xiaofeng Zhu:
The Final Layer Holds the Key: A Unified and Efficient GNN Calibration Framework. CoRR abs/2505.11335 (2025) - [i66]Zhijie Deng, Chris Yuhao Liu, Zirui Pang, Xinlei He, Lei Feng, Qi Xuan, Zhaowei Zhu, Jiaheng Wei:
GUARD: Generation-time LLM Unlearning via Adaptive Restriction and Detection. CoRR abs/2505.13312 (2025) - [i65]Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu:
Understanding Model Reprogramming for CLIP via Decoupling Visual Prompts. CoRR abs/2506.01000 (2025) - [i64]Zesheng Ye, Chengyi Cai, Ruijiang Dong, Jianzhong Qi, Lei Feng, Pin-Yu Chen, Feng Liu:
Neural Network Reprogrammability: A Unified Theme on Model Reprogramming, Prompt Tuning, and Prompt Instruction. CoRR abs/2506.04650 (2025) - [i63]Ming-Kun Xie, Jiahao Xiao, Gang Niu, Lei Feng, Zhiqiang Kou, Min-Ling Zhang, Masashi Sugiyama:
What Makes "Good" Distractors for Object Hallucination Evaluation in Large Vision-Language Models? CoRR abs/2508.06530 (2025) - [i62]Zongqian Wu, Baoduo Xu, Tianyu Li, Zhu Sun, Xiaofeng Zhu, Lei Feng:
Mitigating Strategy-Selection Bias in Reasoning for More Effective Test-Time Scaling. CoRR abs/2509.17905 (2025) - [i61]Zhifang Zhang, Jiahan Zhang, Shengjie Zhou, Qi Wei, Shuo He, Feng Liu, Lei Feng:
Improving Generalizability and Undetectability for Targeted Adversarial Attacks on Multimodal Pre-trained Models. CoRR abs/2509.19994 (2025) - 2024
- [j18]Senlin Shu, Haobo Wang, Zhuowei Wang, Bo Han, Tao Xiang, Bo An, Lei Feng:
Online binary classification from similar and dissimilar data. Mach. Learn. 113(6): 3463-3484 (2024) - [j17]Fei Zhang, Yunjie Ye, Lei Feng, Zhongwen Rao, Jieming Zhu, Marcus Kalander, Chen Gong, Jianye Hao, Bo Han:
Exploiting counter-examples for active learning with partial labels. Mach. Learn. 113(6): 3849-3868 (2024) - [j16]Qi Wei, Lei Feng, Haoliang Sun, Ren Wang, Rundong He, Yilong Yin:
Correction: Learning sample-aware threshold for semi-supervised learning. Mach. Learn. 113(7): 4951 (2024) - [j15]Qi Wei, Lei Feng, Haoliang Sun, Ren Wang, Rundong He, Yilong Yin:
Learning sample-aware threshold for semi-supervised learning. Mach. Learn. 113(8): 5423-5445 (2024) - [j14]Jiaqi Lv, Biao Liu, Lei Feng, Ning Xu, Miao Xu, Bo An, Gang Niu, Xin Geng, Masashi Sugiyama:
On the Robustness of Average Losses for Partial-Label Learning. IEEE Trans. Pattern Anal. Mach. Intell. 46(5): 2569-2583 (2024) - [j13]Haobo Wang, Ruixuan Xiao, Yixuan Li, Lei Feng, Gang Niu, Gang Chen, Junbo Zhao:
PiCO+: Contrastive Label Disambiguation for Robust Partial Label Learning. IEEE Trans. Pattern Anal. Mach. Intell. 46(5): 3183-3198 (2024) - [j12]Senlin Shu, Deng-Bao Wang, Suqin Yuan, Hongxin Wei, Jiuchuan Jiang, Lei Feng, Min-Ling Zhang:
Multiple-instance Learning from Triplet Comparison Bags. ACM Trans. Knowl. Discov. Data 18(4): 90:1-90:18 (2024) - [j11]Haobo Wang, Cheng Peng, Hede Dong, Lei Feng, Weiwei Liu, Tianlei Hu, Ke Chen, Gang Chen:
On the Value of Head Labels in Multi-Label Text Classification. ACM Trans. Knowl. Discov. Data 18(5): 124:1-124:21 (2024) - [c69]Kai Tang, Junbo Zhao, Xiao Ding, Runze Wu, Lei Feng, Gang Chen, Haobo Wang:
Learning Geometry-Aware Representations for New Intent Discovery. ACL (1) 2024: 5641-5654 - [c68]Shuqi Liu, Yuzhou Cao, Qiaozhen Zhang, Lei Feng, Bo An:
Mitigating Underfitting in Learning to Defer with Consistent Losses. AISTATS 2024: 4816-4824 - [c67]Yuzhou Cao, Lei Feng, Bo An:
Consistent Hierarchical Classification with A Generalized Metric. AISTATS 2024: 4825-4833 - [c66]Shiyu Tian, Hongxin Wei, Yiqun Wang, Lei Feng:
CroSel: Cross Selection of Confident Pseudo Labels for Partial-Label Learning. CVPR 2024: 19479-19488 - [c65]Jie Xu, Yazhou Ren, Xiaolong Wang, Lei Feng, Zheng Zhang, Gang Niu, Xiaofeng Zhu:
Investigating and Mitigating the Side Effects of Noisy Views for Self-Supervised Clustering Algorithms in Practical Multi-View Scenarios. CVPR 2024: 22957-22966 - [c64]Ruixuan Xiao, Lei Feng, Kai Tang, Junbo Zhao, Yixuan Li, Gang Chen, Haobo Wang:
Targeted Representation Alignment for Open-World Semi-Supervised Learning. CVPR 2024: 23072-23082 - [c63]Lin Long, Haobo Wang, Zhijie Jiang, Lei Feng, Chang Yao, Gang Chen, Junbo Zhao:
Positive-Unlabeled Learning by Latent Group-Aware Meta Disambiguation. CVPR 2024: 23138-23147 - [c62]Shuo He, Chaojie Wang, Guowu Yang, Lei Feng:
Candidate Label Set Pruning: A Data-centric Perspective for Deep Partial-label Learning. ICLR 2024 - [c61]Zixi Wei, Senlin Shu, Yuzhou Cao, Hongxin Wei, Bo An, Lei Feng:
Consistent Multi-Class Classification from Multiple Unlabeled Datasets. ICLR 2024 - [c60]Suqin Yuan, Lei Feng, Tongliang Liu:
Early Stopping Against Label Noise Without Validation Data. ICLR 2024 - [c59]Shengjie Zhou, Lue Tao, Yuzhou Cao, Tao Xiang, Bo An, Lei Feng:
On the Vulnerability of Adversarially Trained Models Against Two-faced Attacks. ICLR 2024 - [c58]Jinhao Li, Haopeng Li, Sarah Monazam Erfani, Lei Feng, James Bailey, Feng Liu:
Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models. ICML 2024 - [c57]Hao Chen, Jindong Wang, Lei Feng, Xiang Li, Yidong Wang, Xing Xie, Masashi Sugiyama, Rita Singh, Bhiksha Raj:
A General Framework for Learning from Weak Supervision. ICML 2024 - [c56]Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu:
Sample-specific Masks for Visual Reprogramming-based Prompting. ICML 2024 - [c55]Changchun Li, Yuanchao Dai, Lei Feng, Ximing Li, Bing Wang, Jihong Ouyang:
Positive and Unlabeled Learning with Controlled Probability Boundary Fence. ICML 2024 - [c54]Zhenlong Liu, Lei Feng, Huiping Zhuang, Xiaofeng Cao, Hongxin Wei:
Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss. ICML 2024 - [c53]Zixi Wei, Yuzhou Cao, Lei Feng:
Exploiting Human-AI Dependence for Learning to Defer. ICML 2024 - [c52]Jiahan Zhang, Qi Wei, Feng Liu, Lei Feng:
Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data. ICML 2024 - [c51]Chuqiao Zong, Chaojie Wang, Molei Qin, Lei Feng, Xinrun Wang, Bo An:
MacroHFT: Memory Augmented Context-aware Reinforcement Learning On High Frequency Trading. KDD 2024: 4712-4721 - [c50]Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu:
Bayesian-guided Label Mapping for Visual Reprogramming. NeurIPS 2024 - [i60]Chaojie Wang, Yishi Xu, Zhong Peng, Chenxi Zhang, Bo Chen, Xinrun Wang, Lei Feng, Bo An:
keqing: knowledge-based question answering is a nature chain-of-thought mentor of LLM. CoRR abs/2401.00426 (2024) - [i59]Qi Wei, Lei Feng, Haobo Wang, Bo An:
Debiased Sample Selection for Combating Noisy Labels. CoRR abs/2401.13360 (2024) - [i58]Hao Chen, Jindong Wang, Lei Feng, Xiang Li, Yidong Wang, Xing Xie, Masashi Sugiyama, Rita Singh, Bhiksha Raj:
A General Framework for Learning from Weak Supervision. CoRR abs/2402.01922 (2024) - [i57]Huajun Xi, Jianguo Huang, Lei Feng, Hongxin Wei:
Does Confidence Calibration Help Conformal Prediction? CoRR abs/2402.04344 (2024) - [i56]Zhenlong Liu, Lei Feng, Huiping Zhuang, Xiaofeng Cao, Hongxin Wei:
Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss. CoRR abs/2402.05453 (2024) - [i55]Yuyan Zhou, Ye Li, Lei Feng, Sheng-Jun Huang:
Improving Generalization of Deep Neural Networks by Optimum Shifting. CoRR abs/2405.14111 (2024) - [i54]Yuwei Niu, Shuo He, Qi Wei, Feng Liu, Lei Feng:
BDetCLIP: Multimodal Prompting Contrastive Test-Time Backdoor Detection. CoRR abs/2405.15269 (2024) - [i53]Jinhao Li, Haopeng Li, Sarah M. Erfani, Lei Feng, James Bailey, Feng Liu:
Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models. CoRR abs/2406.02915 (2024) - [i52]Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu:
Sample-specific Masks for Visual Reprogramming-based Prompting. CoRR abs/2406.03150 (2024) - [i51]Jiahan Zhang, Qi Wei, Feng Liu, Lei Feng:
Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data. CoRR abs/2406.10502 (2024) - [i50]Chuqiao Zong, Chaojie Wang, Molei Qin, Lei Feng, Xinrun Wang, Bo An:
MacroHFT: Memory Augmented Context-aware Reinforcement Learning On High Frequency Trading. CoRR abs/2406.14537 (2024) - [i49]Beibei Li, Yiyuan Zheng, Beihong Jin, Tao Xiang, Haobo Wang, Lei Feng:
AsyCo: An Asymmetric Dual-task Co-training Model for Partial-label Learning. CoRR abs/2407.15036 (2024) - [i48]Minghao Liu, Zonglin Di, Jiaheng Wei, Zhongruo Wang, Hengxiang Zhang, Ruixuan Xiao, Haoyu Wang, Jinlong Pang, Hao Chen, Ankit Shah, Hongxin Wei, Xinlei He, Zhaowei Zhao, Haobo Wang, Lei Feng, Jindong Wang, James Davis, Yang Liu:
Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond. CoRR abs/2408.11338 (2024) - [i47]Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu:
Bayesian-guided Label Mapping for Visual Reprogramming. CoRR abs/2410.24018 (2024) - [i46]Jincheng Huang, Yujie Mo, Xiaoshuang Shi, Lei Feng, Xiaofeng Zhu:
ELU-GCN: Effectively Label-Utilizing Graph Convolutional Network. CoRR abs/2411.02279 (2024) - [i45]Penghui Yang, Chen-Chen Zong, Sheng-Jun Huang, Lei Feng, Bo An:
Dual-Head Knowledge Distillation: Enhancing Logits Utilization with an Auxiliary Head. CoRR abs/2411.08937 (2024) - [i44]Zongqian Wu, Baoduo Xu, Ruochen Cui, Mengmeng Zhan, Xiaofeng Zhu, Lei Feng:
Rethinking Chain-of-Thought from the Perspective of Self-Training. CoRR abs/2412.10827 (2024) - 2023
- [j10]Fengmao Lv, Jianyang Zhang, Guowu Yang, Lei Feng, Yufeng Yu, Lixin Duan:
Learning cross-domain semantic-visual relationships for transductive zero-shot learning. Pattern Recognit. 141: 109591 (2023) - [j9]Zhuoyi Lin, Lei Feng, Xingzhi Guo, Yu Zhang, Rui Yin, Chee Keong Kwoh, Chi Xu:
COMET: Convolutional Dimension Interaction for Collaborative Filtering. ACM Trans. Intell. Syst. Technol. 14(4): 59:1-59:18 (2023) - [j8]Lei Feng, Senlin Shu, Yuzhou Cao, Lue Tao, Hongxin Wei, Tao Xiang, Bo An, Gang Niu:
Multiple-Instance Learning From Unlabeled Bags With Pairwise Similarity. IEEE Trans. Knowl. Data Eng. 35(11): 11599-11609 (2023) - [j7]Hongxin Wei, Renchunzi Xie, Lei Feng, Bo Han, Bo An:
Deep Learning From Multiple Noisy Annotators as A Union. IEEE Trans. Neural Networks Learn. Syst. 34(12): 10552-10562 (2023) - [c49]Xin Cheng, Deng-Bao Wang, Lei Feng, Min-Ling Zhang, Bo An:
Partial-Label Regression. AAAI 2023: 7140-7147 - [c48]Senlin Shu, Shuo He, Haobo Wang, Hongxin Wei, Tao Xiang, Lei Feng:
A Generalized Unbiased Risk Estimator for Learning with Augmented Classes. AAAI 2023: 9829-9836 - [c47]Shuqi Liu, Yuzhou Cao, Qiaozhen Zhang, Lei Feng, Bo An:
Consistent Complementary-Label Learning via Order-Preserving Losses. AISTATS 2023: 8734-8748 - [c46]Qi Wei, Lei Feng, Haoliang Sun, Ren Wang, Chenhui Guo, Yilong Yin:
Fine-Grained Classification with Noisy Labels. CVPR 2023: 11651-11660 - [c45]Shuo He, Guowu Yang, Lei Feng:
Candidate-aware Selective Disambiguation Based On Normalized Entropy for Instance-dependent Partial-label Learning. ICCV 2023: 1792-1801 - [c44]Suqin Yuan, Lei Feng, Tongliang Liu:
Late Stopping: Avoiding Confidently Learning from Mislabeled Examples. ICCV 2023: 16033-16042 - [c43]Penghui Yang, Ming-Kun Xie, Chen-Chen Zong, Lei Feng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang:
Multi-Label Knowledge Distillation. ICCV 2023: 17225-17234 - [c42]Xin Cheng, Yuzhou Cao, Ximing Li, Bo An, Lei Feng:
Weakly Supervised Regression with Interval Targets. ICML 2023: 5428-5448 - [c41]Zixi Wei, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Xiaofeng Zhu, Heng Tao Shen:
A Universal Unbiased Method for Classification from Aggregate Observations. ICML 2023: 36804-36820 - [c40]Hongxin Wei, Huiping Zhuang, Renchunzi Xie, Lei Feng, Gang Niu, Bo An, Yixuan Li:
Mitigating Memorization of Noisy Labels by Clipping the Model Prediction. ICML 2023: 36868-36886 - [c39]Ruixuan Xiao, Yiwen Dong, Haobo Wang, Lei Feng, Runze Wu, Gang Chen, Junbo Zhao:
ProMix: Combating Label Noise via Maximizing Clean Sample Utility. IJCAI 2023: 4442-4450 - [c38]Shuo He, Lei Feng, Guowu Yang:
Partial-label Learning with Mixed Closed-set and Open-set Out-of-candidate Examples. KDD 2023: 722-731 - [c37]Yuzhou Cao, Hussein Mozannar, Lei Feng, Hongxin Wei, Bo An:
In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer. NeurIPS 2023 - [c36]Xin Cheng, Yuzhou Cao, Haobo Wang, Hongxin Wei, Bo An, Lei Feng:
Regression with Cost-based Rejection. NeurIPS 2023 - [c35]Wei Wang, Lei Feng, Yuchen Jiang, Gang Niu, Min-Ling Zhang, Masashi Sugiyama:
Binary Classification with Confidence Difference. NeurIPS 2023 - [c34]Zhiqing Xiao, Haobo Wang, Ying Jin, Lei Feng, Gang Chen, Fei Huang, Junbo Zhao:
SPA: A Graph Spectral Alignment Perspective for Domain Adaptation. NeurIPS 2023 - [c33]Renchunzi Xie, Hongxin Wei, Lei Feng, Yuzhou Cao, Bo An:
On the Importance of Feature Separability in Predicting Out-Of-Distribution Error. NeurIPS 2023 - [c32]Mingyu Xu, Zheng Lian, Lei Feng, Bin Liu, Jianhua Tao:
ALIM: Adjusting Label Importance Mechanism for Noisy Partial Label Learning. NeurIPS 2023 - [i43]Mingyu Xu, Zheng Lian, Lei Feng, Bin Liu, Jianhua Tao:
DALI: Dynamically Adjusted Label Importance for Noisy Partial Label Learning. CoRR abs/2301.12077 (2023) - [i42]Qi Wei, Lei Feng, Haoliang Sun, Ren Wang, Chenhui Guo, Yilong Yin:
Fine-Grained Classification with Noisy Labels. CoRR abs/2303.02404 (2023) - [i41]Shiyu Tian, Hongxin Wei, Yiqun Wang, Lei Feng:
CroSel: Cross Selection of Confident Pseudo Labels for Partial-Label Learning. CoRR abs/2303.10365 (2023) - [i40]Renchunzi Xie, Hongxin Wei, Yuzhou Cao, Lei Feng, Bo An:
On the Importance of Feature Separability in Predicting Out-Of-Distribution Error. CoRR abs/2303.15488 (2023) - [i39]Jie Xu, Gang Niu, Xiaolong Wang, Yazhou Ren, Lei Feng, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu:
Investigating and Mitigating the Side Effects of Noisy Views in Multi-view Clustering in Practical Scenarios. CoRR abs/2303.17245 (2023) - [i38]Leida Zhang, Yiqun Wang, Zhengda Lu, Lei Feng:
SDFReg: Learning Signed Distance Functions for Point Cloud Registration. CoRR abs/2304.08929 (2023) - [i37]Senlin Shu, Shuo He, Haobo Wang, Hongxin Wei, Tao Xiang, Lei Feng:
A Generalized Unbiased Risk Estimator for Learning with Augmented Classes. CoRR abs/2306.06894 (2023) - [i36]Xin Cheng, Deng-Bao Wang, Lei Feng, Min-Ling Zhang, Bo An:
Partial-Label Regression. CoRR abs/2306.08968 (2023) - [i35]Xin Cheng, Yuzhou Cao, Ximing Li, Bo An, Lei Feng:
Weakly Supervised Regression with Interval Targets. CoRR abs/2306.10458 (2023) - [i34]Zixi Wei, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Xiaofeng Zhu, Heng Tao Shen:
A Universal Unbiased Method for Classification from Aggregate Observations. CoRR abs/2306.11343 (2023) - [i33]Shuo He, Lei Feng, Guowu Yang:
Partial-label Learning with Mixed Closed-set and Open-set Out-of-candidate Examples. CoRR abs/2307.00553 (2023) - [i32]Fei Zhang, Yunjie Ye, Lei Feng, Zhongwen Rao, Jieming Zhu, Marcus Kalander, Chen Gong, Jianye Hao, Bo Han:
Exploiting Counter-Examples for Active Learning with Partial labels. CoRR abs/2307.07413 (2023) - [i31]Penghui Yang, Ming-Kun Xie, Chen-Chen Zong, Lei Feng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang:
Multi-Label Knowledge Distillation. CoRR abs/2308.06453 (2023) - [i30]Suqin Yuan, Lei Feng, Tongliang Liu:
Late Stopping: Avoiding Confidently Learning from Mislabeled Examples. CoRR abs/2308.13862 (2023) - [i29]Wei Wang, Lei Feng, Yuchen Jiang, Gang Niu, Min-Ling Zhang, Masashi Sugiyama:
Binary Classification with Confidence Difference. CoRR abs/2310.05632 (2023) - [i28]Zhiqing Xiao, Haobo Wang, Ying Jin, Lei Feng, Gang Chen, Fei Huang, Junbo Zhao:
SPA: A Graph Spectral Alignment Perspective for Domain Adaptation. CoRR abs/2310.17594 (2023) - [i27]Yuzhou Cao, Hussein Mozannar, Lei Feng, Hongxin Wei, Bo An:
In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer. CoRR abs/2311.01106 (2023) - [i26]Xin Cheng, Yuzhou Cao, Haobo Wang, Hongxin Wei, Bo An, Lei Feng:
Regression with Cost-based Rejection. CoRR abs/2311.04550 (2023) - 2022
- [j6]Lei Feng, Jun Huang, Senlin Shu, Bo An:
Regularized Matrix Factorization for Multilabel Learning With Missing Labels. IEEE Trans. Cybern. 52(5): 3710-3721 (2022) - [j5]Zhuowei Wang, Jing Jiang, Bo Han, Lei Feng, Bo An, Gang Niu, Guodong Long:
SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning. Trans. Mach. Learn. Res. 2022 (2022) - [c31]Lue Tao, Lei Feng, Jinfeng Yi, Songcan Chen:
With False Friends Like These, Who Can Notice Mistakes? AAAI 2022: 8458-8466 - [c30]Renchunzi Xie, Hongxin Wei, Lei Feng, Bo An:
GearNet: Stepwise Dual Learning for Weakly Supervised Domain Adaptation. AAAI 2022: 8717-8725 - [c29]Changchun Li, Ximing Li, Lei Feng, Jihong Ouyang:
Who Is Your Right Mixup Partner in Positive and Unlabeled Learning. ICLR 2022 - [c28]Haobo Wang, Ruixuan Xiao, Yixuan Li, Lei Feng, Gang Niu, Gang Chen, Junbo Zhao:
PiCO: Contrastive Label Disambiguation for Partial Label Learning. ICLR 2022 - [c27]Fei Zhang, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Tao Qin, Masashi Sugiyama:
Exploiting Class Activation Value for Partial-Label Learning. ICLR 2022 - [c26]Hongxin Wei, Lue Tao, Renchunzi Xie, Lei Feng, Bo An:
Open-Sampling: Exploring Out-of-Distribution data for Re-balancing Long-tailed datasets. ICML 2022: 23615-23630 - [c25]Hongxin Wei, Renchunzi Xie, Hao Cheng, Lei Feng, Bo An, Yixuan Li:
Mitigating Neural Network Overconfidence with Logit Normalization. ICML 2022: 23631-23644 - [c24]Shuo He, Lei Feng, Fengmao Lv, Wen Li, Guowu Yang:
Partial Label Learning with Semantic Label Representations. KDD 2022: 545-553 - [c23]Yuzhou Cao, Tianchi Cai, Lei Feng, Lihong Gu, Jinjie Gu, Bo An, Gang Niu, Masashi Sugiyama:
Generalizing Consistent Multi-Class Classification with Rejection to be Compatible with Arbitrary Losses. NeurIPS 2022 - [c22]Lue Tao, Lei Feng, Hongxin Wei, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen:
Can Adversarial Training Be Manipulated By Non-Robust Features? NeurIPS 2022 - [c21]Haobo Wang, Mingxuan Xia, Yixuan Li, Yuren Mao, Lei Feng, Gang Chen, Junbo Zhao:
SoLar: Sinkhorn Label Refinery for Imbalanced Partial-Label Learning. NeurIPS 2022 - [i25]Renchunzi Xie, Hongxin Wei, Lei Feng, Bo An:
GearNet: Stepwise Dual Learning for Weakly Supervised Domain Adaptation. CoRR abs/2201.06001 (2022) - [i24]Haobo Wang, Ruixuan Xiao, Yixuan Li, Lei Feng, Gang Niu, Gang Chen, Junbo Zhao:
PiCO: Contrastive Label Disambiguation for Partial Label Learning. CoRR abs/2201.08984 (2022) - [i23]Lue Tao, Lei Feng, Hongxin Wei, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen:
Can Adversarial Training Be Manipulated By Non-Robust Features? CoRR abs/2201.13329 (2022) - [i22]Hongxin Wei, Renchunzi Xie, Hao Cheng, Lei Feng, Bo An, Yixuan Li:
Mitigating Neural Network Overconfidence with Logit Normalization. CoRR abs/2205.09310 (2022) - [i21]Hongxin Wei, Lue Tao, Renchunzi Xie, Lei Feng, Bo An:
Open-Sampling: Exploring Out-of-Distribution data for Re-balancing Long-tailed datasets. CoRR abs/2206.08802 (2022) - [i20]Haobo Wang, Ruixuan Xiao, Yiwen Dong, Lei Feng, Junbo Zhao:
ProMix: Combating Label Noise via Maximizing Clean Sample Utility. CoRR abs/2207.10276 (2022) - [i19]Haobo Wang, Mingxuan Xia, Yixuan Li, Yuren Mao, Lei Feng, Gang Chen, Junbo Zhao:
SoLar: Sinkhorn Label Refinery for Imbalanced Partial-Label Learning. CoRR abs/2209.10365 (2022) - [i18]Hongxin Wei, Huiping Zhuang, Renchunzi Xie, Lei Feng, Gang Niu, Bo An, Yixuan Li:
Logit Clipping for Robust Learning against Label Noise. CoRR abs/2212.04055 (2022) - 2021
- [b1]Lei Feng:
Advanced topics in weakly supervised learning. Nanyang Technological University, Singapore, 2021 - [j4]Lei Feng, Hongxin Wei, Qingyu Guo, Zhuoyi Lin, Bo An:
Embedding-Augmented Generalized Matrix Factorization for Recommendation With Implicit Feedback. IEEE Intell. Syst. 36(6): 32-41 (2021) - [j3]Zhuoyi Lin, Lei Feng, Rui Yin, Chi Xu, Chee Keong Kwoh:
GLIMG: Global and local item graphs for top-N recommender systems. Inf. Sci. 580: 1-14 (2021) - [j2]Yan Yan, Shining Li, Lei Feng:
Partial multi-label learning with mutual teaching. Knowl. Based Syst. 212: 106624 (2021) - [c20]Tao Liang, Guosheng Lin, Lei Feng, Yan Zhang, Fengmao Lv:
Attention is not Enough: Mitigating the Distribution Discrepancy in Asynchronous Multimodal Sequence Fusion. ICCV 2021: 8128-8136 - [c19]Yuzhou Cao, Lei Feng, Yitian Xu, Bo An, Gang Niu, Masashi Sugiyama:
Learning from Similarity-Confidence Data. ICML 2021: 1272-1282 - [c18]Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama:
Pointwise Binary Classification with Pairwise Confidence Comparisons. ICML 2021: 3252-3262 - [c17]Deng-Bao Wang, Lei Feng, Min-Ling Zhang:
Learning from Complementary Labels via Partial-Output Consistency Regularization. IJCAI 2021: 3075-3081 - [c16]Lei Feng, Senlin Shu, Yuzhou Cao, Lue Tao, Hongxin Wei, Tao Xiang, Bo An, Gang Niu:
Multiple-Instance Learning from Similar and Dissimilar Bags. KDD 2021: 374-382 - [c15]Deng-Bao Wang, Lei Feng, Min-Ling Zhang:
Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence. NeurIPS 2021: 11809-11820 - [c14]Lue Tao, Lei Feng, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen:
Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training. NeurIPS 2021: 16209-16225 - [i17]Lue Tao, Lei Feng, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen:
Provable Defense Against Delusive Poisoning. CoRR abs/2102.04716 (2021) - [i16]Yuzhou Cao, Lei Feng, Yitian Xu, Bo An, Gang Niu, Masashi Sugiyama:
Learning from Similarity-Confidence Data. CoRR abs/2102.06879 (2021) - [i15]Jiaqi Lv, Lei Feng, Miao Xu, Bo An, Gang Niu, Xin Geng, Masashi Sugiyama:
On the Robustness of Average Losses for Partial-Label Learning. CoRR abs/2106.06152 (2021) - [i14]Yuzhou Cao, Lei Feng, Senlin Shu, Yitian Xu, Bo An, Gang Niu, Masashi Sugiyama:
Multi-Class Classification from Single-Class Data with Confidences. CoRR abs/2106.08864 (2021) - 2020
- [c13]Hongxin Wei, Lei Feng, Xiangyu Chen, Bo An:
Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization. CVPR 2020: 13723-13732 - [c12]Lei Feng, Takuo Kaneko, Bo Han, Gang Niu, Bo An, Masashi Sugiyama:
Learning with Multiple Complementary Labels. ICML 2020: 3072-3081 - [c11]Jiaqi Lv, Miao Xu, Lei Feng, Gang Niu, Xin Geng, Masashi Sugiyama:
Progressive Identification of True Labels for Partial-Label Learning. ICML 2020: 6500-6510 - [c10]Lei Feng, Senlin Shu, Zhuoyi Lin, Fengmao Lv, Li Li, Bo An:
Can Cross Entropy Loss Be Robust to Label Noise? IJCAI 2020: 2206-2212 - [c9]Jun Huang, Linchuan Xu, Jing Wang, Lei Feng, Kenji Yamanishi:
Discovering Latent Class Labels for Multi-Label Learning. IJCAI 2020: 3058-3064 - [c8]Lei Feng, Jiaqi Lv, Bo Han, Miao Xu, Gang Niu, Xin Geng, Bo An, Masashi Sugiyama:
Provably Consistent Partial-Label Learning. NeurIPS 2020 - [i13]Jiaqi Lv, Miao Xu, Lei Feng, Gang Niu, Xin Geng, Masashi Sugiyama:
Progressive Identification of True Labels for Partial-Label Learning. CoRR abs/2002.08053 (2020) - [i12]Hongxin Wei, Lei Feng, Xiangyu Chen, Bo An:
Combating noisy labels by agreement: A joint training method with co-regularization. CoRR abs/2003.02752 (2020) - [i11]Jianyang Zhang, Fengmao Lv, Guowu Yang, Lei Feng, Yufeng Yu, Lixin Duan:
Learning Cross-domain Semantic-Visual Relation for Transductive Zero-Shot Learning. CoRR abs/2003.14105 (2020) - [i10]Senlin Shu, Fengmao Lv, Lei Feng, Jun Huang, Shuo He, Jun He, Li Li:
Incorporating Multiple Cluster Centers for Multi-Label Learning. CoRR abs/2004.08113 (2020) - [i9]Lei Feng, Jiaqi Lv, Bo Han, Miao Xu, Gang Niu, Xin Geng, Bo An, Masashi Sugiyama:
Provably Consistent Partial-Label Learning. CoRR abs/2007.08929 (2020) - [i8]Zhuoyi Lin, Lei Feng, Rui Yin, Chi Xu, Chee-Keong Kwoh:
GLIMG: Global and Local Item Graphs for Top-N Recommender Systems. CoRR abs/2007.14018 (2020) - [i7]Zhuoyi Lin, Lei Feng, Xingzhi Guo, Rui Yin, Chee Keong Kwoh, Chi Xu:
COMET: Convolutional Dimension Interaction for Deep Matrix Factorization. CoRR abs/2007.14129 (2020) - [i6]Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama:
Pointwise Binary Classification with Pairwise Confidence Comparisons. CoRR abs/2010.01875 (2020) - [i5]Zhuowei Wang, Jing Jiang, Bo Han, Lei Feng, Bo An, Gang Niu, Guodong Long:
SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning. CoRR abs/2012.00925 (2020) - [i4]Hongxin Wei, Lei Feng, Rundong Wang, Bo An:
MetaInfoNet: Learning Task-Guided Information for Sample Reweighting. CoRR abs/2012.05273 (2020)
2010 – 2019
- 2019
- [c7]Lei Feng, Bo An:
Partial Label Learning with Self-Guided Retraining. AAAI 2019: 3542-3549 - [c6]Lei Feng, Bo An, Shuo He:
Collaboration Based Multi-Label Learning. AAAI 2019: 3550-3557 - [c5]Zhuoyi Lin, Lei Feng, Chee-Keong Kwoh, Chi Xu:
Fast Top-N Personalized Recommendation on Item Graph. IEEE BigData 2019: 3903-3908 - [c4]Lei Feng, Bo An:
Partial Label Learning by Semantic Difference Maximization. IJCAI 2019: 2294-2300 - [c3]Ke Chen, Lei Feng, Qingkuang Chen, Gang Chen, Lidan Shou:
EXACT: Attributed Entity Extraction By Annotating Texts. SIGIR 2019: 1349-1352 - [i3]Lei Feng, Bo An:
Partial Label Learning with Self-Guided Retraining. CoRR abs/1902.03045 (2019) - [i2]Lei Feng, Bo An, Shuo He:
Collaboration based Multi-Label Learning. CoRR abs/1902.03047 (2019) - [i1]Lei Feng, Bo An:
Learning from Multiple Complementary Labels. CoRR abs/1912.12927 (2019) - 2018
- [c2]Shuo He, Lei Feng, Li Li:
Estimating Latent Relative Labeling Importances for Multi-label Learning. ICDM 2018: 1013-1018 - [c1]Lei Feng, Bo An:
Leveraging Latent Label Distributions for Partial Label Learning. IJCAI 2018: 2107-2113 - 2017
- [j1]Yantao Li, Fengtao Xue, Lei Feng, Zehui Qu:
A driving behavior detection system based on a smartphone's built-in sensor. Int. J. Commun. Syst. 30(8) (2017)
Coauthor Index
[c74] [i68] [j18] [j14] [c68] [c67] [c61] [c59] [c51] [i60] [i59] [i50] [i45] [j8] [j7] [c49] [c47] [c42] [c40] [c37] [c36] [c33] [i40] [i36] [i35] [i27] [i26] [j6] [j5] [c30] [c26] [c25] [c23] [i25] [i22] [i21] [i18] [j4] [c19] [c18] [c16] [i16] [i15] [i14] [c13] [c12] [c10] [c8] [i12] [i9] [i6] [i5] [i4] [c7] [c6] [c4] [i3] [i2] [i1] [c1]
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