MIML: A Framework for Learning with Ambiguous Objects - Zhi-Hua Zhou; Min-Ling Zhang; Sheng-Jun Huang; Yufeng Li 008 (CoRR, 2008)

Semi-supervised learning using label mean. - Yufeng Li 008; James T. Kwok; Zhi-Hua Zhou (ICML, 2009)

Learning instance specific distances using metric propagation. - De-Chuan Zhan; Ming Li 005; Yufeng Li 008; Zhi-Hua Zhou (ICML, 2009)

Multi-instance learning by treating instances as non-I.I.D. samples. - Zhi-Hua Zhou; Yu-Yin Sun; Yufeng Li 008 (ICML, 2009)

A Convex Method for Locating Regions of Interest with Multi-instance Learning. - Yufeng Li 008; James T. Kwok; Ivor W. Tsang; Zhi-Hua Zhou (ECML/PKDD (2), 2009)

Tighter and Convex Maximum Margin Clustering. - Yufeng Li 008; Ivor W. Tsang; James Tin-Yau Kwok; Zhi-Hua Zhou (AISTATS, 2009)

Cost-Sensitive Semi-Supervised Support Vector Machine. - Yufeng Li 008; James T. Kwok; Zhi-Hua Zhou (AAAI, 2010)

S4VM: Safe Semi-Supervised Support Vector Machine - Yufeng Li 008; Zhi-Hua Zhou (CoRR, 2010)

Improving Semi-Supervised Support Vector Machines Through Unlabeled Instances Selection. - Yufeng Li 008; Zhi-Hua Zhou (AAAI, 2011)

Diversity Regularized Machine. - Yang Yu 001; Yufeng Li 008; Zhi-Hua Zhou (IJCAI, 2011)

Towards Discovering What Patterns Trigger What Labels. - Yufeng Li 008; Ju-Hua Hu; Yuan Jiang 001; Zhi-Hua Zhou (AAAI, 2012)

Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison. - Tianbao Yang; Yufeng Li 008; Mehrdad Mahdavi; Rong Jin 001; Zhi-Hua Zhou (NIPS, 2012)

Multi-instance multi-label learning. - Zhi-Hua Zhou; Min-Ling Zhang; Sheng-Jun Huang; Yufeng Li 008 (Artif. Intell., 2012)

Multi-Label Learning with PRO Loss. - Miao Xu 001; Yufeng Li 008; Zhi-Hua Zhou (AAAI, 2013)

Convex and scalable weakly labeled SVMs. - Yufeng Li 008; Ivor W. Tsang; James T. Kwok; Zhi-Hua Zhou (J. Mach. Learn. Res., 2013)

Improved Bounds for the Nyström Method With Application to Kernel Classification. - Rong Jin 001; Tianbao Yang; Mehrdad Mahdavi; Yufeng Li 008; Zhi-Hua Zhou (IEEE Trans. Inf. Theory, 2013)

Towards Making Unlabeled Data Never Hurt. - Yufeng Li 008; Zhi-Hua Zhou (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Risk Minimization in the Presence of Label Noise. - Wei Gao 008; Lu Wang 031; Yufeng Li 008; Zhi-Hua Zhou (AAAI, 2016)

Towards Safe Semi-Supervised Learning for Multivariate Performance Measures. - Yufeng Li 008; James T. Kwok; Zhi-Hua Zhou (AAAI, 2016)

Graph Quality Judgement: A Large Margin Expedition. - Yufeng Li 008; Shao-Bo Wang; Zhi-Hua Zhou (IJCAI, 2016)

Kernelized Matrix Factorization for Collaborative Filtering. - Xinyue Liu 003; Charu C. Aggarwal; Yufeng Li 008; Xiangnan Kong; Xinyuan Sun; Saket Sathe 001 (SDM, 2016)

Learning Safe Prediction for Semi-Supervised Regression. - Yufeng Li 008; Han-Wen Zha; Zhi-Hua Zhou (AAAI, 2017)

Learning From Semi-Supervised Weak-Label Data. - Hao-Chen Dong; Yufeng Li 008; Zhi-Hua Zhou (AAAI, 2018)

A General Formulation for Safely Exploiting Weakly Supervised Data. - Lan-Zhe Guo; Yufeng Li 008 (AAAI, 2018)

Large Margin Graph Construction for Semi-Supervised Learning. - Lan-Zhe Guo; Shao-Bo Wang; Yufeng Li 008 (ICDM Workshops, 2018)

Taking Human out of Learning Applications: A Survey on Automated Machine Learning. - Quanming Yao; Mengshuo Wang; Hugo Jair Escalante; Isabelle Guyon; Yi-Qi Hu; Yufeng Li 008; Wei-Wei Tu; Qiang Yang 001; Yang Yu 001 (CoRR, 2018)

Instance selection method for improving graph-based semi-supervised learning. - Hai Wang; Shao-Bo Wang; Yufeng Li 008 (Frontiers Comput. Sci., 2018)

Learning safe multi-label prediction for weakly labeled data. - Tong Wei 001; Lan-Zhe Guo; Yufeng Li 008; Wei Gao 008 (Mach. Learn., 2018)

Towards Automated Semi-Supervised Learning. - Yufeng Li 008; Hai Wang; Tong Wei 001; Wei-Wei Tu (AAAI, 2019)

Learning Compact Model for Large-Scale Multi-Label Data. - Tong Wei 001; Yufeng Li 008 (AAAI, 2019)

Rapid Performance Gain through Active Model Reuse. - Feng Shi; Yufeng Li 008 (IJCAI, 2019)

Partial Label Learning with Unlabeled Data. - Qian-Wei Wang; Yufeng Li 008; Zhi-Hua Zhou (IJCAI, 2019)

Learning for Tail Label Data: A Label-Specific Feature Approach. - Tong Wei 001; Wei-Wei Tu; Yufeng Li 008 (IJCAI, 2019)

Robust Semi-supervised Representation Learning for Graph-Structured Data. - Lan-Zhe Guo; Tao Han; Yufeng Li 008 (PAKDD (3), 2019)

Reliable Weakly Supervised Learning: Maximize Gain and Maintain Safeness. - Lan-Zhe Guo; Yufeng Li 008; Ming Li 005; Jinfeng Yi; Bowen Zhou 001; Zhi-Hua Zhou (CoRR, 2019)

Safe semi-supervised learning: a brief introduction. - Yufeng Li 008; De-Ming Liang (Frontiers Comput. Sci., 2019)

IWE-Net: Instance Weight Network for Locating Negative Comments and its application to improve Traffic User Experience. - Lan-Zhe Guo; Feng Kuang; Zhang-Xun Liu; Yufeng Li 008; Nan Ma; Xiao-Hu Qie (AAAI, 2020)

Learning from Weak-Label Data: A Deep Forest Expedition. - Qian-Wei Wang; Liang Yang; Yufeng Li 008 (AAAI, 2020)

Semi-Supervised Streaming Learning with Emerging New Labels. - Yong-Nan Zhu; Yufeng Li 008 (AAAI, 2020)

Semi-Supervised Graph Embedding via Multi-instance Kernel Learning. - Zhi-Fan Wu; Yufeng Li 008 (BigComp, 2020)

Semi-Supervised Abductive Learning and Its Application to Theft Judicial Sentencing. - Yu-Xuan Huang; Wang-Zhou Dai; Jian Yang; Le-Wen Cai; Shaofen Cheng; Ruizhang Huang; Yufeng Li 008; Zhi-Hua Zhou (ICDM, 2020)

Heterogeneous Mini-Graph Neural Network and Its Application to Fraud Invitation Detection. - Yong-Nan Zhu; Xiaotian Luo; Yufeng Li 008; Bin Bu; Kaibo Zhou; Wenbin Zhang; Mingfan Lu (ICDM, 2020)

Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data. - Lan-Zhe Guo; Zhenyu Zhang; Yuan Jiang 001; Yufeng Li 008; Zhi-Hua Zhou (ICML, 2020)

RECORD: Resource Constrained Semi-Supervised Learning under Distribution Shift. - Lan-Zhe Guo; Zhi Zhou 007; Yufeng Li 008 (KDD, 2020)

Weakly Supervised Learning Meets Ride-Sharing User Experience Enhancement. - Lan-Zhe Guo; Feng Kuang; Zhang-Xun Liu; Yufeng Li 008; Nan Ma; Xiao-Hu Qie (CoRR, 2020)

MixPUL: Consistency-based Augmentation for Positive and Unlabeled Learning. - Tong Wei 001; Feng Shi; Hai Wang; Wei-Wei Tu; Yufeng Li 008 (CoRR, 2020)

Robust Multi-Label Learning with PRO Loss. - Miao Xu 001; Yufeng Li 008; Zhi-Hua Zhou (IEEE Trans. Knowl. Data Eng., 2020)

Does Tail Label Help for Large-Scale Multi-Label Learning? - Tong Wei 001; Yufeng Li 008 (IEEE Trans. Neural Networks Learn. Syst., 2020)

Explanation Consistency Training: Facilitating Consistency-Based Semi-Supervised Learning with Interpretability. - Tao Han; Wei-Wei Tu; Yufeng Li 008 (AAAI, 2021)

NGC: A Unified Framework for Learning with Open-World Noisy Data. - Zhi-Fan Wu; Tong Wei 001; Jianwen Jiang; Chaojie Mao; Mingqian Tang; Yufeng Li 008 (ICCV, 2021)

Dash: Semi-Supervised Learning with Dynamic Thresholding. - Yi Xu 008; Lei Shang; Jinxing Ye; Qi Qian 001; Yufeng Li 008; Baigui Sun; Hao Li 030; Rong Jin 001 (ICML, 2021)

Abductive Learning with Ground Knowledge Base. - Le-Wen Cai; Wang-Zhou Dai; Yu-Xuan Huang; Yufeng Li 008; Stephen H. Muggleton; Yuan Jiang 001 (IJCAI, 2021)

Safe Weakly Supervised Learning. - Yufeng Li 008 (IJCAI, 2021)

Towards Robust Model Reuse in the Presence of Latent Domains. - Jie-Jing Shao; Zhanzhan Cheng; Yufeng Li 008; Shiliang Pu (IJCAI, 2021)

Learning from Imbalanced and Incomplete Supervision with Its Application to Ride-Sharing Liability Judgment. - Lan-Zhe Guo; Zhi Zhou 007; Jie-Jing Shao; Qi Zhang; Feng Kuang; Gao-Le Li; Zhang-Xun Liu; Guobin Wu 001; Nan Ma; Qun (Tracy) Li; Yufeng Li 008 (KDD, 2021)

Probabilistic Label Tree for Streaming Multi-Label Learning. - Tong Wei 001; Jiang-Xin Shi; Yufeng Li 008 (KDD, 2021)

Towards Robust Prediction on Tail Labels. - Tong Wei 001; Wei-Wei Tu; Yufeng Li 008; Guo-Ping Yang (KDD, 2021)

STEP: Out-of-Distribution Detection in the Presence of Limited In-Distribution Labeled Data. - Zhi Zhou 007; Lan-Zhe Guo; Zhanzhan Cheng; Yufeng Li 008; Shiliang Pu (NeurIPS, 2021)

Robust Long-Tailed Learning under Label Noise. - Tong Wei 001; Jiang-Xin Shi; Wei-Wei Tu; Yufeng Li 008 (CoRR, 2021)

Towards Safe Weakly Supervised Learning. - Yufeng Li 008; Lan-Zhe Guo; Zhi-Hua Zhou (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Lightweight Label Propagation for Large-Scale Network Data. - Yufeng Li 008; De-Ming Liang (IEEE Trans. Knowl. Data Eng., 2021)

Interactive Graph Construction for Graph-Based Semi-Supervised Learning. - Changjian Chen; Zhaowei Wang; Jing Wu 004; Xiting Wang; Lan-Zhe Guo; Yufeng Li 008; Shixia Liu (IEEE Trans. Vis. Comput. Graph., 2021)

Class-Imbalanced Semi-Supervised Learning with Adaptive Thresholding. - Lan-Zhe Guo; Yufeng Li 008 (ICML, 2022)

Active Model Adaptation Under Unknown Shift. - Jie-Jing Shao; Yunlu Xu; Zhanzhan Cheng; Yufeng Li 008 (KDD, 2022)

Robust Semi-Supervised Learning when Not All Classes have Labels. - Lan-Zhe Guo; Yi-Ge Zhang; Zhi-Fan Wu; Jie-Jing Shao; Yufeng Li 008 (NeurIPS, 2022)

LOG: Active Model Adaptation for Label-Efficient OOD Generalization. - Jie-Jing Shao; Lan-Zhe Guo; Xiaowen Yang; Yufeng Li 008 (NeurIPS, 2022)

USB: A Unified Semi-supervised Learning Benchmark for Classification. - Yidong Wang; Hao Chen 102; Yue Fan; Wang Sun; Ran Tao 013; Wenxin Hou; Renjie Wang; Linyi Yang; Zhi Zhou 007; Lan-Zhe Guo; Heli Qi; Zhen Wu 002; et al. (NeurIPS, 2022)

Prototypical Classifier for Robust Class-Imbalanced Learning. - Tong Wei 001; Jiang-Xin Shi; Yufeng Li 008; Min-Ling Zhang (PAKDD (2), 2022)

Robust model selection for positive and unlabeled learning with constraints. - Tong Wei 001; Hai Wang; Weiwei Tu; Yufeng Li 008 (Sci. China Inf. Sci., 2022)

LAMDA-SSL: Semi-Supervised Learning in Python. - Lin-Han Jia; Lan-Zhe Guo; Zhi Zhou 007; Yufeng Li 008 (CoRR, 2022)

USB: A Unified Semi-supervised Learning Benchmark. - Yidong Wang; Hao Chen 102; Yue Fan; Wang Sun; Ran Tao 013; Wenxin Hou; Renjie Wang; Linyi Yang; Zhi Zhou 007; Lan-Zhe Guo; Heli Qi; Zhen Wu 002; et al. (CoRR, 2022)

A Survey on Extreme Multi-label Learning. - Tong Wei 001; Zhen Mao; Jiang-Xin Shi; Yufeng Li 008; Min-Ling Zhang (CoRR, 2022)

ODS: Test-Time Adaptation in the Presence of Open-World Data Shift. - Zhi Zhou 007; Lan-Zhe Guo; Lin-Han Jia; Dingchu Zhang; Yufeng Li 008 (ICML, 2023)

Identifying Useful Learnwares for Heterogeneous Label Spaces. - Lan-Zhe Guo; Zhi Zhou 007; Yufeng Li 008; Zhi-Hua Zhou (ICML, 2023)

Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions. - Lin-Han Jia; Lan-Zhe Guo; Zhi Zhou 007; Jie-Jing Shao; Yuke Xiang; Yufeng Li 008 (ICML, 2023)

How Re-sampling Helps for Long-Tail Learning? - Jiang-Xin Shi; Tong Wei 001; Yuke Xiang; Yufeng Li 008 (NeurIPS, 2023)

Parameter-Efficient Long-Tailed Recognition. - Jiang-Xin Shi; Tong Wei 001; Zhi Zhou 007; Xin-Yan Han; Jie-Jing Shao; Yufeng Li 008 (CoRR, 2023)

Investigating the Limitation of CLIP Models: The Worst-Performing Categories. - Jie-Jing Shao; Jiang-Xin Shi; Xiaowen Yang; Lan-Zhe Guo; Yufeng Li 008 (CoRR, 2023)

Safe Abductive Learning in the Presence of Inaccurate Rules. - Xiaowen Yang; Jie-Jing Shao; Wei-Wei Tu; Yufeng Li 008; Wang-Zhou Dai; Zhi-Hua Zhou (AAAI, 2024)

Robust Test-Time Adaptation for Zero-Shot Prompt Tuning. - Dingchu Zhang; Zhi Zhou 007; Yufeng Li 008 (AAAI, 2024)

HONGAT: Graph Attention Networks in the Presence of High-Order Neighbors. - Heng-Kai Zhang; Yi-Ge Zhang; Zhi Zhou 007; Yufeng Li 008 (AAAI, 2024)

Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments. - Lin-Han Jia; Lan-Zhe Guo; Zhi Zhou 007; Yufeng Li 008 (ICLR, 2024)

DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection. - Zhi Zhou 007; Ming Yang; Jiang-Xin Shi; Lan-Zhe Guo; Yufeng Li 008 (ICML, 2024)

Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts. - Jiang-Xin Shi; Tong Wei 001; Zhi Zhou 007; Jie-Jing Shao; Xin-Yan Han; Yufeng Li 008 (ICML, 2024)

Analysis for Abductive Learning and Neural-Symbolic Reasoning Shortcuts. - Xiaowen Yang; Wenda Wei; Jie-Jing Shao; Yufeng Li 008; Zhi-Hua Zhou (ICML, 2024)

LSPAN: Spectrally Localized Augmentation for Graph Consistency Learning. - Heng-Kai Zhang; Yi-Ge Zhang; Zhi Zhou 007; Yufeng Li 008 (IJCAI, 2024)

Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model. - Jiang-Xin Shi; Chi Zhang; Tong Wei 001; Yufeng Li 008 (KDD, 2024)

Vision-Language Models are Strong Noisy Label Detectors. - Tong Wei 001; Hao-Tian Li; Chun-Shu Li; Jiang-Xin Shi; Yufeng Li 008; Min-Ling Zhang (NeurIPS, 2024)

LAMDA-SSL: a comprehensive semi-supervised learning toolkit. - Lin-Han Jia; Lan-Zhe Guo; Zhi Zhou 007; Yufeng Li 008 (Sci. China Inf. Sci., 2024)

LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model. - Zhi Zhou 007; Jiang-Xin Shi; Peng-Xiao Song; Xiaowen Yang; Yi-Xuan Jin; Lan-Zhe Guo; Yufeng Li 008 (CoRR, 2024)

Robustness Assessment of Mathematical Reasoning in the Presence of Missing and Contradictory Conditions. - Shi-Yu Tian; Zhi Zhou 007; Lin-Han Jia; Lan-Zhe Guo; Yufeng Li 008 (CoRR, 2024)

You Only Submit One Image to Find the Most Suitable Generative Model. - Zhi Zhou 007; Lan-Zhe Guo; Peng-Xiao Song; Yufeng Li 008 (CoRR, 2024)

Interactive Reweighting for Mitigating Label Quality Issues. - Weikai Yang; Yukai Guo; Jing Wu 004; Zheng Wang; Lan-Zhe Guo; Yufeng Li 008; Shixia Liu (IEEE Trans. Vis. Comput. Graph., 2024)

Rts: learning robustly from time series data with noisy label. - Zhi Zhou 007; Yi-Xuan Jin; Yufeng Li 008 (Frontiers Comput. Sci., 2024)

Step Back to Leap Forward: Self-Backtracking for Boosting Reasoning of Language Models. - Xiao-Wen Yang; Xuan-Yi Zhu; Wen-Da Wei; Dingchu Zhang; Jie-Jing Shao; Zhi Zhou 007; Lan-Zhe Guo; Yufeng Li 008 (CoRR, 2025)

A Smooth Transition Between Induction and Deduction: Fast Abductive Learning Based on Probabilistic Symbol Perception. - Lin-Han Jia; Si-Yu Han; Lan-Zhe Guo; Zhi Zhou 007; Zhao-Long Li; Yufeng Li 008; Zhi-Hua Zhou (CoRR, 2025)

Micro Text Classification Based on Balanced Positive-Unlabeled Learning. - Lin-Han Jia; Lan-Zhe Guo; Zhi Zhou 007; Si-Ye Han; Zi-Wen Li; Yufeng Li 008 (CoRR, 2025)

Curriculum Abductive Learning. - Wen-Chao Hu; Qi-Jie Li; Lin-Han Jia; Cunjing Ge; Yufeng Li 008; Yuan Jiang 001; Zhi-Hua Zhou (CoRR, 2025)

When Is Prior Knowledge Helpful? Exploring the Evaluation and Selection of Unsupervised Pretext Tasks from a Neuro-Symbolic Perspective. - Lin-Han Jia; Si-Yu Han; Wen-Chao Hu; Jie-Jing Shao; Wen-Da Wei; Zhi Zhou 007; Lan-Zhe Guo; Yufeng Li 008 (CoRR, 2025)

Neuro-Symbolic Artificial Intelligence: Towards Improving the Reasoning Abilities of Large Language Models. - Xiao-Wen Yang; Jie-Jing Shao; Lan-Zhe Guo; Bo-Wen Zhang; Zhi Zhou 007; Lin-Han Jia; Wang-Zhou Dai; Yufeng Li 008 (CoRR, 2025)

Robust semi-supervised learning in open environments. - Lan-Zhe Guo; Lin-Han Jia; Jie-Jing Shao; Yufeng Li 008 (Frontiers Comput. Sci., 2025)