Zhang, Min-Ling

90 publications

NeurIPS 2025 ComRank: Ranking Loss for Multi-Label Complementary Label Learning Jing-Yi Zhu, Yi Gao, Miao Xu, Min-Ling Zhang

AAAI 2025 Evolutionary Classifier Chain for Multi-Dimensional Classification Yu-Yang Zhang, Bin-Bin Jia, Min-Ling Zhang

AAAI 2025 Fast Multi-Instance Partial-Label Learning Yin-Fang Yang, Wei Tang, Min-Ling Zhang

ICML 2025 Generalization Analysis for Controllable Learning Yi-Fan Zhang, Xiao Zhang, Min-Ling Zhang

AISTATS 2025 HACSurv: A Hierarchical Copula-Based Approach for Survival Analysis with Dependent Competing Risks Xin Liu, Weijia Zhang, Min-Ling Zhang

AAAI 2025 Implicit Relative Labeling-Importance Aware Multi-Label Metric Learning Junxiang Mao, Yong Rui, Min-Ling Zhang

ICML 2025 LADA: Scalable Label-Specific CLIP Adapter for Continual Learning Mao-Lin Luo, Zi-Hao Zhou, Tong Wei, Min-Ling Zhang

ICML 2025 Learnware Specification via Dual Alignment Wei Chen, Jun-Xiang Mao, Xiaozheng Wang, Min-Ling Zhang

AAAI 2025 Learnware Specification via Label-Aware Neural Embedding Wei Chen, Junxiang Mao, Min-Ling Zhang

ICLR 2025 Noise Separation Guided Candidate Label Reconstruction for Noisy Partial Label Learning Xiaorui Peng, Yuheng Jia, Fuchao Yang, Ran Wang, Min-Ling Zhang

AAAI 2025 Partial Label Causal Representation Learning for Instance-Dependent Supervision and Domain Generalization Yizhi Wang, Weijia Zhang, Min-Ling Zhang

ICLR 2025 Realistic Evaluation of Deep Partial-Label Learning Algorithms Wei Wang, Dong-Dong Wu, Jindong Wang, Gang Niu, Min-Ling Zhang, Masashi Sugiyama

ICLR 2025 Semi-Supervised CLIP Adaptation by Enforcing Semantic and Trapezoidal Consistency Kai Gan, Bo Ye, Min-Ling Zhang, Tong Wei

ICML 2025 Tight and Fast Bounds for Multi-Label Learning Yi-Fan Zhang, Min-Ling Zhang

ICML 2025 Towards Escaping from Class Dependency Modeling for Multi-Dimensional Classification Teng Huang, Bin-Bin Jia, Min-Ling Zhang

ICML 2025 Weakly-Supervised Contrastive Learning for Imprecise Class Labels Zi-Hao Zhou, Jun-Jie Wang, Tong Wei, Min-Ling Zhang

IJCAI 2025 Wrapped Partial Label Dimensionality Reduction via Dependence Maximization Xiang-Ru Yu, Deng-Bao Wang, Min-Ling Zhang

NeurIPS 2025 X-Mahalanobis: Transformer Feature Mixing for Reliable OOD Detection Tong Wei, Bo-Lin Wang, Jiang-Xin Shi, Yu-Feng Li, Min-Ling Zhang

ICML 2024 Binary Decomposition: A Problem Transformation Perspective for Open-Set Semi-Supervised Learning Jun-Yi Hang, Min-Ling Zhang

IJCAI 2024 Bridging the Gap: Learning Pace Synchronization for Open-World Semi-Supervised Learning Bo Ye, Kai Gan, Tong Wei, Min-Ling Zhang

ICML 2024 Calibration Bottleneck: Over-Compressed Representations Are Less Calibratable Deng-Bao Wang, Min-Ling Zhang

NeurIPS 2024 Continuous Contrastive Learning for Long-Tailed Semi-Supervised Recognition Zi-Hao Zhou, Siyuan Fang, Zi-Jing Zhou, Tong Wei, Yuanyu Wan, Min-Ling Zhang

IJCAI 2024 Deep Multi-Dimensional Classification with Pairwise Dimension-Specific Features Teng Huang, Bin-Bin Jia, Min-Ling Zhang

AAAI 2024 Disentangled Partial Label Learning Wei-Xuan Bao, Yong Rui, Min-Ling Zhang

AAAI 2024 Distilling Reliable Knowledge for Instance-Dependent Partial Label Learning Dong-Dong Wu, Deng-Bao Wang, Min-Ling Zhang

AAAI 2024 EAT: Towards Long-Tailed Out-of-Distribution Detection Tong Wei, Bo-Lin Wang, Min-Ling Zhang

CVPR 2024 Efficient Model Stealing Defense with Noise Transition Matrix Dong-Dong Wu, Chilin Fu, Weichang Wu, Wenwen Xia, Xiaolu Zhang, Jun Zhou, Min-Ling Zhang

IJCAI 2024 Exploiting Conjugate Label Information for Multi-Instance Partial-Label Learning Wei Tang, Weijia Zhang, Min-Ling Zhang

NeurIPS 2024 Generalization Analysis for Label-Specific Representation Learning Yi-Fan Zhang, Min-Ling Zhang

ICML 2024 Generalization Analysis for Multi-Label Learning Yifan Zhang, Min-Ling Zhang

ICML 2024 Learning Label Shift Correction for Test-Agnostic Long-Tailed Recognition Tong Wei, Zhen Mao, Zi-Hao Zhou, Yuanyu Wan, Min-Ling Zhang

IJCAI 2024 Learning Label-Specific Multiple Local Metrics for Multi-Label Classification Junxiang Mao, Jun-Yi Hang, Min-Ling Zhang

AAAI 2024 Long-Tailed Partial Label Learning by Head Classifier and Tail Classifier Cooperation Yuheng Jia, Xiaorui Peng, Ran Wang, Min-Ling Zhang

NeurIPS 2024 Multi-Instance Partial-Label Learning with Margin Adjustment Wei Tang, Yin-Fang Yang, Zhaofei Wang, Weijia Zhang, Min-Ling Zhang

NeurIPS 2024 Multi-Label Open Set Recognition Yi-Bo Wang, Jun-Yi Hang, Min-Ling Zhang

MLJ 2024 Partial Label Learning with Emerging New Labels Xiang-Ru Yu, Deng-Bao Wang, Min-Ling Zhang

IJCAI 2024 Unlearning from Weakly Supervised Learning Yi Tang, Yi Gao, Yonggang Luo, Jucheng Yang, Miao Xu, Min-Ling Zhang

NeurIPS 2024 Vision-Language Models Are Strong Noisy Label Detectors Tong Wei, Hao-Tian Li, Chun-Shu Li, Jiang-Xin Shi, Yu-Feng Li, Min-Ling Zhang

NeurIPS 2024 What Makes Partial-Label Learning Algorithms Effective? Jiaqi Lv, Yangfan Liu, Shiyu Xia, Ning Xu, Miao Xu, Gang Niu, Min-Ling Zhang, Masashi Sugiyama, Xin Geng

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

AAAI 2023 Can Label-Specific Features Help Partial-Label Learning? Ruo-Jing Dong, Jun-Yi Hang, Tong Wei, Min-Ling Zhang

NeurIPS 2023 Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning Wei Tang, Weijia Zhang, Min-Ling Zhang

NeurIPSW 2023 Instance-Dependent Partial Label Learning with Identifiable Causal Representations Yizhi Wang, Weijia Zhang, Min-Ling Zhang

IJCAI 2023 Label Specific Multi-Semantics Metric Learning for Multi-Label Classification: Global Consideration Helps Junxiang Mao, Wei Wang, Min-Ling Zhang

ICML 2023 Nearly-Tight Bounds for Deep Kernel Learning Yifan Zhang, Min-Ling Zhang

CVPR 2023 On the Pitfall of Mixup for Uncertainty Calibration Deng-Bao Wang, Lanqing Li, Peilin Zhao, Pheng-Ann Heng, Min-Ling Zhang

NeurIPS 2023 Partial Multi-Label Learning with Probabilistic Graphical Disambiguation Jun-Yi Hang, Min-Ling Zhang

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

IJCAI 2023 Progressive Label Propagation for Semi-Supervised Multi-Dimensional Classification Teng Huang, Bin-Bin Jia, Min-Ling Zhang

IJCAI 2023 Stochastic Feature Averaging for Learning with Long-Tailed Noisy Labels Hao-Tian Li, Tong Wei, Hao Yang, Kun Hu, Chong Peng, Li-Bo Sun, Xun-Liang Cai, Min-Ling Zhang

IJCAI 2023 Unbiased Risk Estimator to Multi-Labeled Complementary Label Learning Yi Gao, Miao Xu, Min-Ling Zhang

ICML 2022 Dual Perspective of Label-Specific Feature Learning for Multi-Label Classification Jun-Yi Hang, Min-Ling Zhang

AAAI 2022 End-to-End Probabilistic Label-Specific Feature Learning for Multi-Label Classification Jun-Yi Hang, Min-Ling Zhang, Yanghe Feng, Xiaocheng Song

NeurIPS 2022 Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization Weijia Zhang, Xuanhui Zhang, Hanwen Deng, Min-Ling Zhang

NeurIPS 2022 One Positive Label Is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement Ning Xu, Congyu Qiao, Jiaqi Lv, Xin Geng, Min-Ling Zhang

ICML 2022 Revisiting Consistency Regularization for Deep Partial Label Learning Dong-Dong Wu, Deng-Bao Wang, Min-Ling Zhang

IJCAI 2021 BAMBOO: A Multi-Instance Multi-Label Approach Towards VDI User Logon Behavior Modeling Wen-Ping Fan, Yao Zhang, Qichen Hao, Xinya Wu, Min-Ling Zhang

IJCAI 2021 Correlation-Guided Representation for Multi-Label Text Classification Qian-Wen Zhang, Ximing Zhang, Zhao Yan, Ruifang Liu, Yunbo Cao, Min-Ling Zhang

ICML 2021 Discriminative Complementary-Label Learning with Weighted Loss Yi Gao, Min-Ling Zhang

AAAI 2021 Exploiting Unlabeled Data via Partial Label Assignment for Multi-Class Semi-Supervised Learning Zhen-Ru Zhang, Qian-Wen Zhang, Yunbo Cao, Min-Ling Zhang

NeurIPS 2021 Instance-Dependent Partial Label Learning Ning Xu, Congyu Qiao, Xin Geng, Min-Ling Zhang

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

AAAI 2021 Learning from Noisy Labels with Complementary Loss Functions Deng-Bao Wang, Yong Wen, Lujia Pan, Min-Ling Zhang

ICML 2021 Multi-Dimensional Classification via Sparse Label Encoding Bin-Bin Jia, Min-Ling Zhang

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

AAAI 2020 Maximum Margin Multi-Dimensional Classification Bin-Bin Jia, Min-Ling Zhang

AAAI 2020 Multi-View Partial Multi-Label Learning with Graph-Based Disambiguation Ze-Sen Chen, Xuan Wu, Qing-Guo Chen, Yao Hu, Min-Ling Zhang

NeurIPS 2020 Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization Wei Wang, Min-Ling Zhang

AAAI 2019 CAFE: Adaptive VDI Workload Prediction with Multi-Grained Features Yao Zhang, Wen-Ping Fan, Xuan Wu, Hua Chen, Bin-Yang Li, Min-Ling Zhang

AAAI 2019 Multi-Dimensional Classification via kNN Feature Augmentation Bin-Bin Jia, Min-Ling Zhang

ACML 2019 Multi-Label Learning with Regularization Enriched Label-Specific Features Ze-Sen Chen, Min-Ling Zhang

IJCAI 2019 Multi-View Multi-Label Learning with View-Specific Information Extraction Xuan Wu, Qing-Guo Chen, Yao Hu, Dengbao Wang, Xiaodong Chang, Xiaobo Wang, Min-Ling Zhang

AAAI 2019 Partial Multi-Label Learning via Credible Label Elicitation Jun-Peng Fang, Min-Ling Zhang

MLJ 2019 Supervised Representation Learning for Multi-Label Classification Ming Huang, Fuzhen Zhuang, Xiao Zhang, Xiang Ao, Zhengyu Niu, Min-Ling Zhang, Qing He

AAAI 2018 Feature-Induced Labeling Information Enrichment for Multi-Label Learning Qian-Wen Zhang, Yun Zhong, Min-Ling Zhang

IJCAI 2018 Towards Enabling Binary Decomposition for Partial Label Learning Xuan Wu, Min-Ling Zhang

IJCAI 2017 Binary Linear Compression for Multi-Label Classification Wen-Ji Zhou, Yang Yu, Min-Ling Zhang

AAAI 2017 Confidence-Rated Discriminative Partial Label Learning Cai-Zhi Tang, Min-Ling Zhang

MLJ 2017 Maximum Margin Partial Label Learning Fei Yu, Min-Ling Zhang

ACML 2017 Preface Min-Ling Zhang, Yung-Kyun Noh

AAAI 2016 Multi-Label Manifold Learning Peng Hou, Xin Geng, Min-Ling Zhang

ACML 2015 Maximum Margin Partial Label Learning Fei Yu, Min-Ling Zhang

IJCAI 2015 Solving the Partial Label Learning Problem: An Instance-Based Approach Min-Ling Zhang, Fei Yu

IJCAI 2015 Towards Class-Imbalance Aware Multi-Label Learning Min-Ling Zhang, Yu-Kun Li, Xu-Ying Liu

ACML 2013 Multi-Label Classification with Unlabeled Data: An Inductive Approach Le Wu, Min-Ling Zhang

MLJ 2012 Introduction to the Special Issue on Learning from Multi-Label Data Grigorios Tsoumakas, Min-Ling Zhang, Zhi-Hua Zhou

IJCAI 2011 LIFT: Multi-Label Learning with Label-Specific Features Min-Ling Zhang

AAAI 2007 Multi-Label Learning by Instance Differentiation Min-Ling Zhang, Zhi-Hua Zhou

NeurIPS 2006 Multi-Instance Multi-Label Learning with Application to Scene Classification Zhi-Li Zhang, Min-ling Zhang

ECML-PKDD 2003 Ensembles of Multi-Instance Learners Zhi-Hua Zhou, Min-Ling Zhang