Min-Ling Zhang

发表

A Review on Multi-Label Learning Algorithms

Min-Ling Zhang, Zhi-Hua Zhou, 2014, IEEE Transactions on Knowledge and Data Engineering.

CoTrade: Confident Co-Training With Data Editing

Zhi-Hua Zhou, Min-Ling Zhang, Min-Ling Zhang, 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Solving multi-instance problems with classifier ensemble based on constructive clustering

Zhi-Hua Zhou, Min-Ling Zhang, Min-Ling Zhang, 2007, Knowledge and Information Systems.

Neural Networks for Multi-Instance Learning

Zhi-Hua Zhou, Min-Ling Zhang, Min-Ling Zhang, 2002 .

Feature selection for multi-label naive Bayes classification

Víctor Robles, Min-Ling Zhang, José María Peña Sánchez, 2009, Inf. Sci..

Exploiting unlabeled data to enhance ensemble diversity

Zhi-Hua Zhou, Min-Ling Zhang, Min-Ling Zhang, 2009, 2010 IEEE International Conference on Data Mining.

Solving the Multi-Instance Problem with Neural Networks

Zhi-Hua Zhou, Min-Ling Zhang, Min-Ling Zhang, 2003 .

M 3 M IML : A Maximum Margin Method for Multi-Instance Multi-Label Learning

Min-Ling Zhang, 2008 .

One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement

Min-Ling Zhang, Jiaqi Lv, Xin Geng, 2022, ArXiv.

Artificial Intelligence: Second CCF International Conference, ICAI 2019, Xuzhou, China, August 22-23, 2019, Proceedings

Min-Ling Zhang, M. Rey, Kevin Knight, 2019, Communications in Computer and Information Science.

Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization

Min-Ling Zhang, Weijia Zhang, Xuanhui Zhang, 2022, 2202.12570.

Stable Label-Specific Features Generation for Multi-Label Learning via Mixture-Based Clustering Ensemble

Min-Ling Zhang, Yi-Bo Wang, Jun-Yi Hang, 2022, IEEE/CAA Journal of Automatica Sinica.

Multi-label Classification with High-rank and High-order Label Correlations

Min-Ling Zhang, Yuheng Jia, Yang Feng, 2022, ArXiv.

Dual Perspective of Label-Specific Feature Learning for Multi-Label Classification

Min-Ling Zhang, Jun-Yi Hang, 2022, ICML.

Submodular Feature Selection for Partial Label Learning

Min-Ling Zhang, Jun-Yi Hang, Wei-Xuan Bao, 2022, KDD.

Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization

Min-Ling Zhang, Weijia Zhang, Xuanhui Zhang, 2022, NeurIPS.

One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement

Min-Ling Zhang, Jiaqi Lv, Xin Geng, 2022, NeurIPS.

A Survey on Extreme Multi-label Learning

Min-Ling Zhang, Yu-Feng Li, Tong Wei, 2022, ArXiv.

Multi-Instance Partial-Label Learning: Towards Exploiting Dual Inexact Supervision

Min-Ling Zhang, Wei Tang, Weijia Zhang, 2022, Sci. China Inf. Sci..

Binary relevance for multi-label learning: an overview

Min-Ling Zhang, Yukun Li, Xin Geng, 2018, Frontiers of Computer Science.

Multi-dimensional Classification via Selective Feature Augmentation

Min-Ling Zhang, B. Jia, Bin-Bin Jia, 2022, Machine Intelligence Research.

Weakly Supervised Part-of-Speech (POS) Tagging without Disambiguation

Min-Ling Zhang, Deyu Zhou, Yulan He, 2017 .

Tac-Valuer: Knowledge-based Stroke Evaluation in Table Tennis

Yingcai Wu, Min-Ling Zhang, Dazhen Deng, 2021, KDD.

Multilabel Neural Networks with Applications to Functional Genomics and Text Categorization

Zhi-Hua Zhou, Min-Ling Zhang, Min-Ling Zhang, 2006, IEEE Transactions on Knowledge and Data Engineering.

Multi-Instance Multi-Label Learning with Application to Scene Classification

Zhi-Hua Zhou, Min-Ling Zhang, Min-Ling Zhang, 2006, NIPS.

ML-KNN: A lazy learning approach to multi-label learning

Zhi-Hua Zhou, Min-Ling Zhang, Min-Ling Zhang, 2007, Pattern Recognit..

Multi-Label Manifold Learning

Xin Geng, Min-Ling Zhang, Peng Hou, 2016, AAAI.

Multi-instance multi-label learning

Zhi-Hua Zhou, Min-Ling Zhang, Sheng-Jun Huang, 2008, Artif. Intell..

A k-Nearest Neighbor Based Multi-Instance Multi-Label Learning Algorithm

Min-Ling Zhang, Min-Ling Zhang, 2010, 2010 22nd IEEE International Conference on Tools with Artificial Intelligence.

MIMLRBF: RBF neural networks for multi-instance multi-label learning

Min-Ling Zhang, Zhi-Jian Wang, Min-Ling Zhang, 2009, Neurocomputing.

Generalized Multi-Instance Learning: Problems, Algorithms and Data Sets

Min-Ling Zhang, Min-Ling Zhang, 2009, 2009 WRI Global Congress on Intelligent Systems.

M3MIML: A Maximum Margin Method for Multi-instance Multi-label Learning

Zhi-Hua Zhou, Min-Ling Zhang, Min-Ling Zhang, 2008, 2008 Eighth IEEE International Conference on Data Mining.

M 3 M IML : A Maximum Margin Method for Multi-Instance Multi-Label Learning

Min-Ling Zhang, 2008 .

Multi-Label Learning by Instance Differentiation

Zhi-Hua Zhou, Min-Ling Zhang, Min-Ling Zhang, 2007, AAAI.

Transfer synthetic over-sampling for class-imbalance learning with limited minority class data

Xu-Ying Liu, Min-Ling Zhang, Sheng-Tao Wang, 2019, Frontiers of Computer Science.

CAFE and SOUP: Toward Adaptive VDI Workload Prediction

Min-Ling Zhang, Xinya Wu, Yao Zhang, 2022, ACM Trans. Intell. Syst. Technol..

CAFE: Adaptive VDI Workload Prediction with Multi-Grained Features

Hua Chen, Xuan Wu, Min-Ling Zhang, 2019, AAAI.

A k-nearest neighbor based algorithm for multi-label classification

Zhi-Hua Zhou, Min-Ling Zhang, Min-Ling Zhang, 2005, 2005 IEEE International Conference on Granular Computing.

Classifier Ensemble with Unlabeled Data pdf

Zhi-Hua Zhou, Min-Ling Zhang, Min-Ling Zhang, 2009, ArXiv.

Instance-Dependent Partial Label Learning pdf

Xin Geng, Min-Ling Zhang, Congyu Qiao, 2021, NeurIPS.

Discriminative Complementary-Label Learning with Weighted Loss

Min-Ling Zhang, Yi Gao, Min-Ling Zhang, 2021, ICML.

Multi-instance clustering with applications to multi-instance prediction

Zhi-Hua Zhou, Min-Ling Zhang, Min-Ling Zhang, 2009, Applied Intelligence.

Disambiguation-Free Partial Label Learning

Min-Ling Zhang, Min-Ling Zhang, Fei Yu, 2017, IEEE Transactions on Knowledge and Data Engineering.

Enhancing Binary Relevance for Multi-label Learning with Controlled Label Correlations Exploitation

Min-Ling Zhang, Yu-Kun Li, Min-Ling Zhang, 2014, PRICAI.

Multi-label learning by exploiting label dependency

Kun Zhang, Min-Ling Zhang, Min-Ling Zhang, 2010, KDD.

Weakly Supervised POS Tagging without Disambiguation

Deyu Zhou, Yulan He, Min-Ling Zhang, 2018, ACM Trans. Asian Low Resour. Lang. Inf. Process..

Lift: Multi-Label Learning with Label-Specific Features

Min-Ling Zhang, Min-Ling Zhang, 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Partial Label Dimensionality Reduction via Confidence-Based Dependence Maximization

Min-Ling Zhang, Wei-Xuan Bao, Jun-Yi Hang, 2021, KDD.

Disambiguation Enabled Linear Discriminant Analysis for Partial Label Dimensionality Reduction

Min-Ling Zhang, Jing-Han Wu, Min-Ling Zhang, 2019, KDD.

Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence

Min-Ling Zhang, Lei Feng, Deng-Bao Wang, 2021, NeurIPS.

Collaborative Learning of Label Semantics and Deep Label-Specific Features for Multi-Label Classification

Min-Ling Zhang, Jun-Yi Hang, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Leveraging Implicit Relative Labeling-Importance Information for Effective Multi-label Learning

Xin Geng, Min-Ling Zhang, Yu-Kun Li, 2015, 2015 IEEE International Conference on Data Mining.

Compositional metric learning for multi-label classification

Min-Ling Zhang, Yan-Ping Sun, Min-Ling Zhang, 2020, Frontiers of Computer Science.

Learning from Noisy Labels with Complementary Loss Functions

Min-Ling Zhang, Lujia Pan, Yong Wen, 2021, AAAI.

Inductive Semi-supervised Multi-Label Learning with Co-Training

Wang Zhan, Min-Ling Zhang, Min-Ling Zhang, 2017, KDD.

Adaptive Graph Guided Disambiguation for Partial Label Learning

Li Li, Min-Ling Zhang, Dengbao Wang, 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Revisiting Consistency Regularization for Deep Partial Label Learning

Min-Ling Zhang, Deng-Bao Wang, Dong-Dong Wu, 2022, ICML.

Maximum margin partial label learning

Fei Yu, Min-Ling Zhang, Min-Ling Zhang, 2017, Machine Learning.

Multi-dimensional Classification via Selective Feature Augmentation

Min-Ling Zhang, Bin-Bin Jia, 2022, Int. J. Autom. Comput..

Towards Class-Imbalance Aware Multi-Label Learning

Xu-Ying Liu, Min-Ling Zhang, Yu-Kun Li, 2015, IEEE Transactions on Cybernetics.

Transformer-based Multi-Instance Learning for Weakly Supervised Object Detection

Min-Ling Zhang, Weijia Zhang, Zhaofei Wang, 2023, ArXiv.

Towards Learning Causal Representations from Multi-Instance Bags

Min-Ling Zhang, Weijia Zhang, Xuanhui Zhang, 2022, ArXiv.

Ensembles of Multi-Instance Neural Networks

Zhi-Hua Zhou, Min-Ling Zhang, Min-Ling Zhang, 2004, Intelligent Information Processing.

Improve Multi-Instance Neural Networks through Feature Selection

Zhi-Hua Zhou, Min-Ling Zhang, Min-Ling Zhang, 2004, Neural Processing Letters.

Rethinking the Value of Labels for Instance-Dependent Label Noise Learning

Min-Ling Zhang, Weijia Zhang, Hanwen Deng, 2023, ArXiv.

Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization

Wei Wang, Min-Ling Zhang, Min-Ling Zhang, 2020, NeurIPS.

Partial Label Learning via Feature-Aware Disambiguation

Xu-Ying Liu, Min-Ling Zhang, Bin-Bin Zhou, 2016, KDD.

Solving the Partial Label Learning Problem: An Instance-Based Approach

Fei Yu, Min-Ling Zhang, Min-Ling Zhang, 2015, IJCAI.

BiLabel-Specific Features for Multi-Label Classification

Min-Ling Zhang, Jun-Peng Fang, Yi-Bo Wang, 2021, ACM Trans. Knowl. Discov. Data.

Binary relevance for multi-label learning: an overview

Xin Geng, Xu-Ying Liu, Min-Ling Zhang, 2018, Frontiers of Computer Science.

Feature-Induced Manifold Disambiguation for Multi-View Partial Multi-label Learning

Yao Hu, Min-Ling Zhang, Xuan Wu, 2020, KDD.

BAMBOO: A Multi-instance Multi-label Approach Towards VDI User Logon Behavior Modeling

Min-Ling Zhang, Wen-Ping Fan, Yao Zhang, 2021, IJCAI.

Correlation-Guided Representation for Multi-Label Text Classification

Min-Ling Zhang, Yunbo Cao, Qian-Wen Zhang, 2021, IJCAI.

Multi-View Multi-Label Learning with View-Specific Information Extraction

Xiaobo Wang, Min-Ling Zhang, Xuan Wu, 2019, IJCAI.

Multi-Label Classification With Label-Specific Feature Generation: A Wrapped Approach

Min-Ling Zhang, Zeping Yu, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Multi-Label Learning with Regularization Enriched Label-Specific Features

Min-Ling Zhang, Ze-Sen Chen, Min-Ling Zhang, 2019, ACML.

A Survey of Learning on Small Data: Generalization, Optimization, and Challenge

I. Tsang, J. Kwok, Min-Ling Zhang, 2022, 2207.14443.

Multi-Dimensional Classification via Decomposed Label Encoding

Min-Ling Zhang, Bin-Bin Jia, Min-Ling Zhang, 2023, IEEE Transactions on Knowledge and Data Engineering.

Md-knn: An Instance-based Approach for Multi-Dimensional Classification

Min-Ling Zhang, Bin-Bin Jia, Min-Ling Zhang, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

Multi-dimensional classification via stacked dependency exploitation

Min-Ling Zhang, Bin-Bin Jia, Min-Ling Zhang, 2020, Science China Information Sciences.

Maximum Margin Multi-Dimensional Classification

Min-Ling Zhang, Bin-Bin Jia, Min-Ling Zhang, 2020, IEEE Transactions on Neural Networks and Learning Systems.

Multi-Dimensional Classification via kNN Feature Augmentation

Min-Ling Zhang, Bin-Bin Jia, Min-Ling Zhang, 2019, AAAI.

Multi-Dimensional Classification via Sparse Label Encoding

Min-Ling Zhang, Bin-Bin Jia, Min-Ling Zhang, 2021, ICML.

Large-scale multi-label classification using unknown streaming images

Yin Wang, Xu-Ying Liu, Yu Zhang, 2020, Pattern Recognit..

Complementary Classifier Induced Partial Label Learning

Min-Ling Zhang, Yuheng Jia, Chongjie Si, 2023, ArXiv.

Partial Label Learning with Discrimination Augmentation

Min-Ling Zhang, W. Wang, 2022, KDD.

Towards Mitigating the Class-Imbalance Problem for Partial Label Learning

Jing Wang, Min-Ling Zhang, Min-Ling Zhang, 2018, KDD.

Towards Enabling Binary Decomposition for Partial Label Learning

Xuan Wu, Min-Ling Zhang, Min-Ling Zhang, 2018, IJCAI.

Confidence-Rated Discriminative Partial Label Learning

Min-Ling Zhang, Cai-Zhi Tang, Min-Ling Zhang, 2017, AAAI.

Multi-Label Neural Networks with Applications to Functional Genomics and Text Categorization

Min-Ling Zhang, Zhi-Hua Zhou, 2006, IEEE Trans. Knowl. Data Eng..

Complementary to Multiple Labels: A Correlation-Aware Correction Approach

Min-Ling Zhang, Miao Xu, Yi Gao, 2023, ArXiv.

Multi-dimensional multi-label classification: Towards encompassing heterogeneous label spaces and multi-label annotations

Min-Ling Zhang, Bin-Bin Jia, 2023, Pattern Recognit..

Supervised representation learning for multi-label classification

Fuzhen Zhuang, Qing He, Xiao Zhang, 2019, Machine Learning.

Binary Linear Compression for Multi-label Classification

Yang Yu, Min-Ling Zhang, Wen-Ji Zhou, 2017, IJCAI.

Ml-rbf: RBF Neural Networks for Multi-Label Learning

Min-Ling Zhang, Min-Ling Zhang, 2009, Neural Processing Letters.

MIML: A Framework for Learning with Ambiguous Objects pdf

Zhi-Hua Zhou, Min-Ling Zhang, Sheng-Jun Huang, 2008, ArXiv.

Decomposition-Based Classifier Chains for Multi-Dimensional Classification

Min-Ling Zhang, Bin-Bin Jia, 2022, IEEE Transactions on Artificial Intelligence.

Multi-label Learning

Zhi-Hua Zhou, Min-Ling Zhang, Min-Ling Zhang, 2017, Encyclopedia of Machine Learning and Data Mining.

Partial Multi-Label Learning via Credible Label Elicitation

Min-Ling Zhang, Jun-Peng Fang, Min-Ling Zhang, 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Feature-Induced Labeling Information Enrichment for Multi-Label Learning

Min-Ling Zhang, Yun Zhong, Qian-Wen Zhang, 2018, AAAI.

Learning from Complementary Labels via Partial-Output Consistency Regularization

Min-Ling Zhang, Lei Feng, Deng-Bao Wang, 2021, IJCAI.

Multi-View Partial Multi-Label Learning with Graph-Based Disambiguation

Yao Hu, Xuan Wu, Ze-Sen Chen, 2020, AAAI.

Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning

Min-Ling Zhang, Wei Tang, Weijia Zhang, 2023, ArXiv.

Exploiting Unlabeled Data via Partial Label Assignment for Multi-Class Semi-Supervised Learning

Min-Ling Zhang, Yunbo Cao, Zhen-Ru Zhang, 2021, AAAI.

Prototypical Classifier for Robust Class-Imbalanced Learning pdf

Min-Ling Zhang, Tong Wei, Yu-Feng Li, 2021, PAKDD.

On the Pitfall of Mixup for Uncertainty Calibration

Min-Ling Zhang, P. Zhao, P. Heng, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Progressive Label Propagation for Semi-Supervised Multi-Dimensional Classification

Min-Ling Zhang, T. Huang, Bin-Bin Jia, 2023, IJCAI.

Nearly-tight Bounds for Deep Kernel Learning

Min-Ling Zhang, YiFan Zhang, 2023, ICML.

Robust Representation Learning for Unreliable Partial Label Learning

Min-Ling Zhang, Xin Geng, Yuge Shi, 2023, ArXiv.

Partial-Label Regression

Min-Ling Zhang, Lei Feng, Bo An, 2023, AAAI.

Adapting RBF Neural Networks to Multi-Instance Learning

Zhi-Hua Zhou, Min-Ling Zhang, Min-Ling Zhang, 2006, Neural Processing Letters.

Multilabel Neural Networks with Applications to Functional Genomics and Text Categorization

Min-Ling Zhang, Zhi-Hua Zhou, 2006, IEEE Transactions on Knowledge and Data Engineering.

Unbiased Risk Estimator to Multi-Labeled Complementary Label Learning

Min-Ling Zhang, Miao Xu, Yi Gao, 2023, IJCAI.

Data sparse nonparametric regression with-insensitive losses : supplementary material

Min-Ling Zhang, Olivier Fercoq, Maxime Sangnier, 2017 .

Stochastic Feature Averaging for Learning with Long-Tailed Noisy Labels

Min-Ling Zhang, Hao Li, Kun Hu, 2023, IJCAI.

Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning

Min-Ling Zhang, Wei Tang, Weijia Zhang, 2023, NeurIPS.

Learning from Noisy Labels via Dynamic Loss Thresholding pdf

Xin Geng, Min-Ling Zhang, Lei Miao, 2021, IEEE Transactions on Knowledge and Data Engineering.

Towards Enabling Binary Decomposition for Partial Label Learning

Min-Ling Zhang, X. Wu, 2018, IJCAI.

Can Label-Specific Features Help Partial-Label Learning?

Min-Ling Zhang, Tong Wei, Jun-Yi Hang, 2023, AAAI.

Partial label learning with emerging new labels

Min-Ling Zhang, Xiang-Ru Yu, Deng-Bao Wang, 2022, Machine Learning.

Solving multi-instance problems with classifier ensemble based on constructive clustering

Min-Ling Zhang, Zhi-Hua Zhou, 2007, Knowledge and Information Systems.

Towards Class-Imbalance Aware Multi-Label Learning

Min-Ling Zhang, Yukun Li, Xu-Ying Liu, 2015, IEEE Transactions on Cybernetics.

A novel bag generator for image database retrieval with multi-instance learning techniques

Zhi-Hua Zhou, Ke-Jia Chen, Min-Ling Zhang, 2003, Proceedings. 15th IEEE International Conference on Tools with Artificial Intelligence.

Tac-Valuer: Knowledge-based Stroke Evaluation in Table Tennis

Min-Ling Zhang, Yingcai Wu, Yu-Xuan Huang, 2021, KDD.

Label Specific Multi-Semantics Metric Learning for Multi-Label Classification: Global Consideration Helps

Min-Ling Zhang, W. Wang, Junxiang Mao, 2023, International Joint Conference on Artificial Intelligence.

End-to-End Probabilistic Label-Specific Feature Learning for Multi-Label Classification

Min-Ling Zhang, Jun-Yi Hang, Xiaocheng Song, 2022, AAAI.

A new R2 indicator for better hypervolume approximation

Hisao Ishibuchi, Min-Ling Zhang, Ke Shang, 2018, GECCO.

Multi-Label Classification with Unlabeled Data: An Inductive Approach

Le Wu, Min-Ling Zhang, Min-Ling Zhang, 2013, ACML.