Yu-Feng Li

ORCID

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 80

Top Venues

Publications

Jie-Jing Shao, Hao-Sen Shi, Lan-Zhe Guo, Yu-Feng Li
Offline Imitation Learning with Model-based Reverse Augmentation. KDD (2024)
Weikai Yang, Yukai Guo, Jing Wu, Zheng Wang, Lan-Zhe Guo, Yu-Feng Li, Shixia Liu
Interactive Reweighting for Mitigating Label Quality Issues. IEEE Trans. Vis. Comput. Graph. 30 (3) (2024)
Zhi Zhou, Yi-Xuan Jin, Yu-Feng Li
Rts: learning robustly from time series data with noisy label. Frontiers Comput. Sci. 18 (6) (2024)
Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Yu-Feng Li
Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments. ICLR (2024)
Zhi Zhou, Ming Yang, Jiang-Xin Shi, Lan-Zhe Guo, Yu-Feng Li
DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection. CoRR (2024)
Shi-Yu Tian, Zhi Zhou, Lin-Han Jia, Lan-Zhe Guo, Yu-Feng Li
Robustness Assessment of Mathematical Reasoning in the Presence of Missing and Contradictory Conditions. CoRR (2024)
Jie-Jing Shao, Hao-Sen Shi, Lan-Zhe Guo, Yu-Feng Li
Offline Imitation Learning with Model-based Reverse Augmentation. CoRR (2024)
Jiang-Xin Shi, Chi Zhang, Tong Wei, Yu-Feng Li
Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model. CoRR (2024)
Zhi Zhou, Jiang-Xin Shi, Peng-Xiao Song, Xiaowen Yang, Yi-Xuan Jin, Lan-Zhe Guo, Yu-Feng Li
LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model. CoRR (2024)
Jiang-Xin Shi, Chi Zhang, Tong Wei, Yu-Feng Li
Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model. KDD (2024)
Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Jie-Jing Shao, Yuke Xiang, Yu-Feng Li
Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions. ICML (2023)
Jiang-Xin Shi, Tong Wei, Yuke Xiang, Yu-Feng Li
How Re-sampling Helps for Long-Tail Learning? CoRR (2023)
Jiang-Xin Shi, Tong Wei, Yuke Xiang, Yu-Feng Li
How Re-sampling Helps for Long-Tail Learning? NeurIPS (2023)
Zhi Zhou, Lan-Zhe Guo, Lin-Han Jia, Dingchu Zhang, Yu-Feng Li
ODS: Test-Time Adaptation in the Presence of Open-World Data Shift. ICML (2023)
Jie-Jing Shao, Jiang-Xin Shi, Xiaowen Yang, Lan-Zhe Guo, Yu-Feng Li
Investigating the Limitation of CLIP Models: The Worst-Performing Categories. CoRR (2023)
Weikai Yang, Yukai Guo, Jing Wu, Zheng Wang, Lan-Zhe Guo, Yu-Feng Li, Shixia Liu
Interactive Reweighting for Mitigating Label Quality Issues. CoRR (2023)
Lan-Zhe Guo, Zhi Zhou, Yu-Feng Li, Zhi-Hua Zhou
Identifying Useful Learnwares for Heterogeneous Label Spaces. ICML (2023)
Jiang-Xin Shi, Tong Wei, Zhi Zhou, Xin-Yan Han, Jie-Jing Shao, Yu-Feng Li
Parameter-Efficient Long-Tailed Recognition. CoRR (2023)
Yidong Wang, Hao Chen, Yue Fan, Wang Sun, Ran Tao, Wenxin Hou, Renjie Wang, Linyi Yang, Zhi Zhou, Lan-Zhe Guo, Heli Qi, Zhen Wu, Yu-Feng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jindong Wang, Xing Xie, Yue Zhang
USB: A Unified Semi-supervised Learning Benchmark for Classification. NeurIPS (2022)
Lan-Zhe Guo, Yu-Feng Li
Class-Imbalanced Semi-Supervised Learning with Adaptive Thresholding. ICML (2022)
Jie-Jing Shao, Lan-Zhe Guo, Xiaowen Yang, Yu-Feng Li
LOG: Active Model Adaptation for Label-Efficient OOD Generalization. NeurIPS (2022)
Jie-Jing Shao, Yunlu Xu, Zhanzhan Cheng, Yu-Feng Li
Active Model Adaptation Under Unknown Shift. KDD (2022)
Lan-Zhe Guo, Zhi Zhou, Yu-Feng Li
Robust Deep Semi-Supervised Learning: A Brief Introduction. CoRR (2022)
Tong Wei, Zhen Mao, Jiang-Xin Shi, Yu-Feng Li, Min-Ling Zhang
A Survey on Extreme Multi-label Learning. CoRR (2022)
Lan-Zhe Guo, Yi-Ge Zhang, Zhi-Fan Wu, Jie-Jing Shao, Yu-Feng Li
Robust Semi-Supervised Learning when Not All Classes have Labels. NeurIPS (2022)
Tong Wei, Jiang-Xin Shi, Yu-Feng Li, Min-Ling Zhang
Prototypical Classifier for Robust Class-Imbalanced Learning. PAKDD (2) (2022)
Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Yu-Feng Li
LAMDA-SSL: Semi-Supervised Learning in Python. CoRR (2022)
Yidong Wang, Hao Chen, Yue Fan, Wang Sun, Ran Tao, Wenxin Hou, Renjie Wang, Linyi Yang, Zhi Zhou, Lan-Zhe Guo, Heli Qi, Zhen Wu, Yu-Feng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jindong Wang, Xing Xie, Yue Zhang
USB: A Unified Semi-supervised Learning Benchmark. CoRR (2022)
Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yu-Feng Li, Baigui Sun, Hao Li, Rong Jin
Dash: Semi-Supervised Learning with Dynamic Thresholding. ICML (2021)
Tong Wei, Jiang-Xin Shi, Wei-Wei Tu, Yu-Feng Li
Robust Long-Tailed Learning under Label Noise. CoRR (2021)
Tong Wei, Wei-Wei Tu, Yu-Feng Li, Guo-Ping Yang
Towards Robust Prediction on Tail Labels. KDD (2021)
Zhi Zhou, Lan-Zhe Guo, Zhanzhan Cheng, Yu-Feng Li, Shiliang Pu
STEP: Out-of-Distribution Detection in the Presence of Limited In-Distribution Labeled Data. NeurIPS (2021)
Le-Wen Cai, Wang-Zhou Dai, Yu-Xuan Huang, Yu-Feng Li, Stephen Muggleton, Yuan Jiang
Abductive Learning with Ground Knowledge Base. IJCAI (2021)
Lan-Zhe Guo, Zhi Zhou, Jie-Jing Shao, Qi Zhang, Feng Kuang, Gao-Le Li, Zhang-Xun Liu, Guobin Wu, Nan Ma, Qun Li, Yu-Feng Li
Learning from Imbalanced and Incomplete Supervision with Its Application to Ride-Sharing Liability Judgment. KDD (2021)
Changjian Chen, Zhaowei Wang, Jing Wu, Xiting Wang, Lan-Zhe Guo, Yu-Feng Li, Shixia Liu
Interactive Graph Construction for Graph-Based Semi-Supervised Learning. IEEE Trans. Vis. Comput. Graph. 27 (9) (2021)
Yu-Feng Li
Safe Weakly Supervised Learning. IJCAI (2021)
Jie-Jing Shao, Zhanzhan Cheng, Yu-Feng Li, Shiliang Pu
Towards Robust Model Reuse in the Presence of Latent Domains. IJCAI (2021)
Tao Han, Wei-Wei Tu, Yu-Feng Li
Explanation Consistency Training: Facilitating Consistency-Based Semi-Supervised Learning with Interpretability. AAAI (2021)
Yu-Feng Li, Lan-Zhe Guo, Zhi-Hua Zhou
Towards Safe Weakly Supervised Learning. IEEE Trans. Pattern Anal. Mach. Intell. 43 (1) (2021)
Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yu-Feng Li, Baigui Sun, Hao Li, Rong Jin
Dash: Semi-Supervised Learning with Dynamic Thresholding. CoRR (2021)
Zhi-Fan Wu, Tong Wei, Jianwen Jiang, Chaojie Mao, Mingqian Tang, Yu-Feng Li
NGC: A Unified Framework for Learning with Open-World Noisy Data. ICCV (2021)
Yu-Feng Li, De-Ming Liang
Lightweight Label Propagation for Large-Scale Network Data. IEEE Trans. Knowl. Data Eng. 33 (5) (2021)
Zhi-Fan Wu, Tong Wei, Jianwen Jiang, Chaojie Mao, Mingqian Tang, Yu-Feng Li
NGC: A Unified Framework for Learning with Open-World Noisy Data. CoRR (2021)
Tong Wei, Jiang-Xin Shi, Yu-Feng Li
Probabilistic Label Tree for Streaming Multi-Label Learning. KDD (2021)
Tong Wei, Jiang-Xin Shi, Yu-Feng Li, Min-Ling Zhang
Prototypical Classifier for Robust Class-Imbalanced Learning. CoRR (2021)
Lan-Zhe Guo, Feng Kuang, Zhang-Xun Liu, Yu-Feng Li, Nan Ma, Xiao-Hu Qie
IWE-Net: Instance Weight Network for Locating Negative Comments and its application to improve Traffic User Experience. AAAI (2020)
Lan-Zhe Guo, Zhi Zhou, Yu-Feng Li
RECORD: Resource Constrained Semi-Supervised Learning under Distribution Shift. KDD (2020)
Min-Ling Zhang, Yu-Feng Li, Qi Liu
Preface. J. Comput. Sci. Technol. 35 (2) (2020)
Qian-Wei Wang, Liang Yang, Yu-Feng Li
Learning from Weak-Label Data: A Deep Forest Expedition. AAAI (2020)
Yu-Xuan Huang, Wang-Zhou Dai, Jian Yang, Le-Wen Cai, Shaofen Cheng, Ruizhang Huang, Yu-Feng Li, Zhi-Hua Zhou
Semi-Supervised Abductive Learning and Its Application to Theft Judicial Sentencing. ICDM (2020)
Tong Wei, Feng Shi, Hai Wang, Wei-Wei Tu, Yu-Feng Li
MixPUL: Consistency-based Augmentation for Positive and Unlabeled Learning. CoRR (2020)
Yong-Nan Zhu, Xiaotian Luo, Yu-Feng Li, Bin Bu, Kaibo Zhou, Wenbin Zhang, Mingfan Lu
Heterogeneous Mini-Graph Neural Network and Its Application to Fraud Invitation Detection. ICDM (2020)
Zhi-Fan Wu, Yu-Feng Li
Semi-Supervised Graph Embedding via Multi-instance Kernel Learning. BigComp (2020)
Miao Xu, Yu-Feng Li, Zhi-Hua Zhou
Robust Multi-Label Learning with PRO Loss. IEEE Trans. Knowl. Data Eng. 32 (8) (2020)
Tong Wei, Yu-Feng Li
Does Tail Label Help for Large-Scale Multi-Label Learning? IEEE Trans. Neural Networks Learn. Syst. 31 (7) (2020)
Yong-Nan Zhu, Yu-Feng Li
Semi-Supervised Streaming Learning with Emerging New Labels. AAAI (2020)
Lan-Zhe Guo, Zhenyu Zhang, Yuan Jiang, Yu-Feng Li, Zhi-Hua Zhou
Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data. ICML (2020)
Lan-Zhe Guo, Feng Kuang, Zhang-Xun Liu, Yu-Feng Li, Nan Ma, Xiao-Hu Qie
Weakly Supervised Learning Meets Ride-Sharing User Experience Enhancement. CoRR (2020)
Feng Shi, Yu-Feng Li
Rapid Performance Gain through Active Model Reuse. IJCAI (2019)
Yu-Feng Li, Hai Wang, Tong Wei, Wei-Wei Tu
Towards Automated Semi-Supervised Learning. AAAI (2019)
Tong Wei, Wei-Wei Tu, Yu-Feng Li
Learning for Tail Label Data: A Label-Specific Feature Approach. IJCAI (2019)
Lan-Zhe Guo, Yu-Feng Li, Ming Li, Jinfeng Yi, Bowen Zhou, Zhi-Hua Zhou
Reliable Weakly Supervised Learning: Maximize Gain and Maintain Safeness. CoRR (2019)
Lan-Zhe Guo, Tao Han, Yu-Feng Li
Robust Semi-supervised Representation Learning for Graph-Structured Data. PAKDD (3) (2019)
Tong Wei, Yu-Feng Li
Learning Compact Model for Large-Scale Multi-Label Data. AAAI (2019)
Yu-Feng Li, De-Ming Liang
Safe semi-supervised learning: a brief introduction. Frontiers Comput. Sci. 13 (4) (2019)
Qian-Wei Wang, Yu-Feng Li, Zhi-Hua Zhou
Partial Label Learning with Unlabeled Data. IJCAI (2019)
Hao-Chen Dong, Yu-Feng Li, Zhi-Hua Zhou
Learning From Semi-Supervised Weak-Label Data. AAAI (2018)
Tong Wei, Yu-Feng Li
Does Tail Label Help for Large-Scale Multi-Label Learning. IJCAI (2018)
Quanming Yao, Mengshuo Wang, Hugo Jair Escalante, Isabelle Guyon, Yi-Qi Hu, Yu-Feng Li, Wei-Wei Tu, Qiang Yang, Yang Yu
Taking Human out of Learning Applications: A Survey on Automated Machine Learning. CoRR (2018)
Lan-Zhe Guo, Shao-Bo Wang, Yu-Feng Li
Large Margin Graph Construction for Semi-Supervised Learning. ICDM Workshops (2018)
Tong Wei, Lan-Zhe Guo, Yu-Feng Li, Wei Gao
Learning safe multi-label prediction for weakly labeled data. Mach. Learn. 107 (4) (2018)
De-Ming Liang, Yu-Feng Li
Lightweight Label Propagation for Large-Scale Network Data. IJCAI (2018)
Hai Wang, Shao-Bo Wang, Yu-Feng Li
Instance selection method for improving graph-based semi-supervised learning. Frontiers Comput. Sci. 12 (4) (2018)
Lan-Zhe Guo, Yu-Feng Li
A General Formulation for Safely Exploiting Weakly Supervised Data. AAAI (2018)
Yu-Feng Li, Han-Wen Zha, Zhi-Hua Zhou
Learning Safe Prediction for Semi-Supervised Regression. AAAI (2017)
Xinyue Liu, Charu C. Aggarwal, Yu-Feng Li, Xiangnan Kong, Xinyuan Sun, Saket Sathe
Kernelized Matrix Factorization for Collaborative Filtering. SDM (2016)
Yu-Feng Li, Shao-Bo Wang, Zhi-Hua Zhou
Graph Quality Judgement: A Large Margin Expedition. IJCAI (2016)
Wei Gao, Lu Wang, Yu-Feng Li, Zhi-Hua Zhou
Risk Minimization in the Presence of Label Noise. AAAI (2016)
Hai Wang, Shao-Bo Wang, Yu-Feng Li
Instance Selection Method for Improving Graph-Based Semi-supervised Learning. PRICAI (2016)
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou
Towards Safe Semi-Supervised Learning for Multivariate Performance Measures. AAAI (2016)
Yu-Feng Li, Zhi-Hua Zhou
Towards Making Unlabeled Data Never Hurt. IEEE Trans. Pattern Anal. Mach. Intell. 37 (1) (2015)
Yu-Feng Li, Ivor W. Tsang, James T. Kwok, Zhi-Hua Zhou
Convex and Scalable Weakly Labeled SVMs CoRR (2013)
Yu-Feng Li, Ivor W. Tsang, James T. Kwok, Zhi-Hua Zhou
Convex and scalable weakly labeled SVMs. J. Mach. Learn. Res. 14 (1) (2013)
Miao Xu, Yu-Feng Li, Zhi-Hua Zhou
Multi-Label Learning with PRO Loss. AAAI (2013)
Rong Jin, Tianbao Yang, Mehrdad Mahdavi, Yu-Feng Li, Zhi-Hua Zhou
Improved Bounds for the Nyström Method With Application to Kernel Classification. IEEE Trans. Inf. Theory 59 (10) (2013)
Tianbao Yang, Yu-Feng Li, Mehrdad Mahdavi, Rong Jin, Zhi-Hua Zhou
Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison. NIPS (2012)
Yu-Feng Li, Ju-Hua Hu, Yuan Jiang, Zhi-Hua Zhou
Towards Discovering What Patterns Trigger What Labels. AAAI (2012)
Zhi-Hua Zhou, Min-Ling Zhang, Sheng-Jun Huang, Yu-Feng Li
Multi-instance multi-label learning. Artif. Intell. 176 (1) (2012)
Yu-Feng Li, Zhi-Hua Zhou
Towards Making Unlabeled Data Never Hurt. ICML (2011)
Yu-Feng Li, Zhi-Hua Zhou
Improving Semi-Supervised Support Vector Machines Through Unlabeled Instances Selection. AAAI (2011)
Yang Yu, Yu-Feng Li, Zhi-Hua Zhou
Diversity Regularized Machine. IJCAI (2011)
Yu-Feng Li, Zhi-Hua Zhou
S4VM: Safe Semi-Supervised Support Vector Machine CoRR (2010)
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou
Cost-Sensitive Semi-Supervised Support Vector Machine. AAAI (2010)
Zhi-Hua Zhou, Yu-Yin Sun, Yu-Feng Li
Multi-instance learning by treating instances as non-I.I.D. samples. ICML (2009)
Yu-Feng Li, Ivor W. Tsang, James Tin-Yau Kwok, Zhi-Hua Zhou
Tighter and Convex Maximum Margin Clustering. AISTATS (2009)
Yu-Feng Li, James T. Kwok, Ivor W. Tsang, Zhi-Hua Zhou
A Convex Method for Locating Regions of Interest with Multi-instance Learning. ECML/PKDD (2) (2009)
De-Chuan Zhan, Ming Li, Yu-Feng Li, Zhi-Hua Zhou
Learning instance specific distances using metric propagation. ICML (2009)
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou
Semi-supervised learning using label mean. ICML (2009)
Zhi-Hua Zhou, Yu-Yin Sun, Yu-Feng Li
Multi-Instance Learning by Treating Instances As Non-I.I.D. Samples CoRR (2008)
Zhi-Hua Zhou, Min-Ling Zhang, Sheng-Jun Huang, Yu-Feng Li
MIML: A Framework for Learning with Ambiguous Objects CoRR (2008)

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Publication Activity (10 Years)

Top Topics

Top Venues

Yu-Feng Li