Min-ling Zhang

Classifier-induced Reciprocal Points for Multi-label Open-set Recognition AAAI 2026 APVR: Hour-Level Long Video Understanding with Adaptive Pivot Visual Information Retrieval AAAI 2026 Collaborative Dual Representations for Semi-Supervised Partial Label Learning AAAI 2026 Realistic Evaluation of Deep Partial-Label Learning Algorithms ICLR 2025 Weakly-Supervised Contrastive Learning for Imprecise Class Labels ICML 2025 Semi-Supervised CLIP Adaptation by Enforcing Semantic and Trapezoidal Consistency ICLR 2025 Noise Separation guided Candidate Label Reconstruction for Noisy Partial Label Learning ICLR 2025 Generalization Analysis for Controllable Learning ICML 2025 Tight and Fast Bounds for Multi-Label Learning ICML 2025 LADA: Scalable Label-Specific CLIP Adapter for Continual Learning ICML 2025 Wrapped Partial Label Dimensionality Reduction via Dependence Maximization IJCAI 2025 Learnware Specification via Label-Aware Neural Embedding AAAI 2025 Implicit Relative Labeling-Importance Aware Multi-Label Metric Learning AAAI 2025 Partial Label Causal Representation Learning for Instance-Dependent Supervision and Domain Generalization AAAI 2025 Fast Multi-Instance Partial-Label Learning AAAI 2025 Evolutionary Classifier Chain for Multi-Dimensional Classification AAAI 2025 Towards Escaping from Class Dependency Modeling for Multi-Dimensional Classification ICML 2025 Learnware Specification via Dual Alignment ICML 2025 HACSurv: A Hierarchical Copula-Based Approach for Survival Analysis with Dependent Competing Risks AISTATS 2025 Efficient Model Stealing Defense with Noise Transition Matrix CVPR 2024 EAT: Towards Long-Tailed Out-of-Distribution Detection AAAI 2024 Distilling Reliable Knowledge for Instance-Dependent Partial Label Learning AAAI 2024 Learning Label Shift Correction for Test-Agnostic Long-Tailed Recognition ICML 2024 Generalization Analysis for Multi-Label Learning ICML 2024 Bridging the Gap: Learning Pace Synchronization for Open-World Semi-Supervised Learning IJCAI 2024 Disentangled Partial Label Learning AAAI 2024 Long-Tailed Partial Label Learning by Head Classifier and Tail Classifier Cooperation AAAI 2024 Binary Decomposition: A Problem Transformation Perspective for Open-Set Semi-Supervised Learning ICML 2024 Calibration Bottleneck: Over-compressed Representations are Less Calibratable ICML 2024 Multi-Label Open Set Recognition NIPS 2024 Multi-Instance Partial-Label Learning with Margin Adjustment NIPS 2024 Continuous Contrastive Learning for Long-Tailed Semi-Supervised Recognition NIPS 2024 Vision-Language Models are Strong Noisy Label Detectors NIPS 2024 What Makes Partial-Label Learning Algorithms Effective? NIPS 2024 Generalization Analysis for Label-Specific Representation Learning NIPS 2024 Unlearning from Weakly Supervised Learning IJCAI 2024 Exploiting Conjugate Label Information for Multi-Instance Partial-Label Learning IJCAI 2024 Learning Label-Specific Multiple Local Metrics for Multi-Label Classification IJCAI 2024 Deep Multi-Dimensional Classification with Pairwise Dimension-Specific Features IJCAI 2024 Label Specific Multi-Semantics Metric Learning for Multi-Label Classification: Global Consideration Helps IJCAI 2023 Partial Multi-Label Learning with Probabilistic Graphical Disambiguation NIPS 2023 Binary Classification with Confidence Difference NIPS 2023 Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning NIPS 2023 Partial-Label Regression AAAI 2023 Can Label-Specific Features Help Partial-Label Learning? AAAI 2023 On the Pitfall of Mixup for Uncertainty Calibration CVPR 2023 Nearly-tight Bounds for Deep Kernel Learning ICML 2023 Unbiased Risk Estimator to Multi-Labeled Complementary Label Learning IJCAI 2023 Progressive Label Propagation for Semi-Supervised Multi-Dimensional Classification IJCAI 2023 Stochastic Feature Averaging for Learning with Long-Tailed Noisy Labels IJCAI 2023 Dual Perspective of Label-Specific Feature Learning for Multi-Label Classification ICML 2022 One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement NIPS 2022 Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization NIPS 2022 Revisiting Consistency Regularization for Deep Partial Label Learning ICML 2022 End-to-End Probabilistic Label-Specific Feature Learning for Multi-Label Classification AAAI 2022 Multi-Dimensional Classification via Sparse Label Encoding ICML 2021 Exploiting Unlabeled Data via Partial Label Assignment for Multi-Class Semi-Supervised Learning AAAI 2021 Learning from Noisy Labels with Complementary Loss Functions AAAI 2021 BAMBOO: A Multi-instance Multi-label Approach Towards VDI User Logon Behavior Modeling IJCAI 2021 Learning from Complementary Labels via Partial-Output Consistency Regularization IJCAI 2021 Correlation-Guided Representation for Multi-Label Text Classification IJCAI 2021 Instance-Dependent Partial Label Learning NIPS 2021 Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence NIPS 2021 Discriminative Complementary-Label Learning with Weighted Loss ICML 2021 Maximum Margin Multi-Dimensional Classification AAAI 2020 Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization NIPS 2020 Multi-View Partial Multi-Label Learning with Graph-Based Disambiguation AAAI 2020 Partial Multi-Label Learning via Credible Label Elicitation AAAI 2019 Multi-Label Learning with Regularization Enriched Label-Specific Features ACML 2019 CAFE: Adaptive VDI Workload Prediction with Multi-Grained Features AAAI 2019 Multi-Dimensional Classification via kNN Feature Augmentation AAAI 2019 Multi-View Multi-Label Learning with View-Specific Information Extraction IJCAI 2019 Towards Enabling Binary Decomposition for Partial Label Learning IJCAI 2018 Binary Linear Compression for Multi-label Classification IJCAI 2017 Solving the Partial Label Learning Problem: An Instance-Based Approach IJCAI 2015 Maximum Margin Partial Label Learning ACML 2015 Towards Class-Imbalance Aware Multi-Label Learning IJCAI 2015 Multi-Label Classification with Unlabeled Data: An Inductive Approach ACML 2013 Multi-Instance Multi-Label Learning with Application to Scene Classification NIPS 2006