Min-Ling Zhang

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Submodular Feature Selection for Partial Label Learning.

[BibT_eX]

[DOI]

Wei-Xuan Bao

Jun-Yi Hang

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Partial Label Learning with Gradually Induced Error-Correction Output Codes.

[BibT_eX]

[DOI]

Yu-Xuan Shi

Proceedings of the Neural Information Processing - 29th International Conference, 2022

Revisiting Consistency Regularization for Deep Partial Label Learning.

[BibT_eX]

[DOI]

Dong-Dong Wu

Proceedings of the International Conference on Machine Learning, 2022

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

[BibT_eX]

[DOI]

Jun-Yi Hang

Proceedings of the International Conference on Machine Learning, 2022

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

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Leveraging Implicit Relative Labeling-Importance Information for Effective Multi-Label Learning.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2021

Partial Multi-Label Learning via Credible Label Elicitation.

[BibT_eX]

[DOI]

Jun-Peng Fang

IEEE Trans. Pattern Anal. Mach. Intell., 2021

Preface.

[BibT_eX]

[DOI]

Sheng-Jun Huang

Mingsheng Long

J. Comput. Sci. Technol., 2021

Compositional metric learning for multi-label classification.

[BibT_eX]

[DOI]

Yan-Ping Sun

Frontiers Comput. Sci., 2021

Learning from Noisy Labels via Dynamic Loss Thresholding.

[BibT_eX]

[DOI]

CoRR, 2021

Instance-Dependent Partial Label Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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

[BibT_eX]

[DOI]

Lei Feng

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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

[BibT_eX]

[DOI]

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Partial Label Dimensionality Reduction via Confidence-Based Dependence Maximization.

[BibT_eX]

[DOI]

Wei-Xuan Bao

Jun-Yi Hang

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Correlation-Guided Representation for Multi-Label Text Classification.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Learning from Complementary Labels via Partial-Output Consistency Regularization.

[BibT_eX]

[DOI]

Lei Feng

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

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

[BibT_eX]

[DOI]

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Multi-Dimensional Classification via Sparse Label Encoding.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Discriminative Complementary-Label Learning with Weighted Loss.

[BibT_eX]

[DOI]

Yi Gao

Proceedings of the 38th International Conference on Machine Learning, 2021

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

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Learning from Noisy Labels with Complementary Loss Functions.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Large-scale multi-label classification using unknown streaming images.

[BibT_eX]

[DOI]

Pattern Recognit., 2020

Multi-dimensional classification via <i>k</i>NN feature augmentation.

[BibT_eX]

[DOI]

Pattern Recognit., 2020

Preface.

[BibT_eX]

[DOI]

Yu-Feng Li

Qi Liu

J. Comput. Sci. Technol., 2020

Multi-dimensional classification via stacked dependency exploitation.

[BibT_eX]

[DOI]

Sci. China Inf. Sci., 2020

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

[BibT_eX]

[DOI]

Wei Wang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

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

[BibT_eX]

[DOI]

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

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

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Pattern Recognition, 2020

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

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Neighborhood kinship preserving hashing for supervised learning.

[BibT_eX]

[DOI]

Signal Process. Image Commun., 2019

Supervised representation learning for multi-label classification.

[BibT_eX]

[DOI]

Mach. Learn., 2019

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

[BibT_eX]

[DOI]

Sheng-Tao Wang

Frontiers Comput. Sci., 2019

Disambiguation Enabled Linear Discriminant Analysis for Partial Label Dimensionality Reduction.

[BibT_eX]

[DOI]

Jing-Han Wu

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

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

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Multi-Label Learning with Regularization Enriched Label-Specific Features.

[BibT_eX]

[DOI]

Ze-Sen Chen

Proceedings of The 11th Asian Conference on Machine Learning, 2019

CAFE: Adaptive VDI Workload Prediction with Multi-Grained Features.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Multi-Dimensional Classification via kNN Feature Augmentation.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Weakly Supervised POS Tagging without Disambiguation.

[BibT_eX]

[DOI]

ACM Trans. Asian Low Resour. Lang. Inf. Process., 2018

Binary relevance for multi-label learning: an overview.

[BibT_eX]

[DOI]

Frontiers Comput. Sci., 2018

Towards Mitigating the Class-Imbalance Problem for Partial Label Learning.

[BibT_eX]

[DOI]

Jing Wang

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Towards Enabling Binary Decomposition for Partial Label Learning.

[BibT_eX]

[DOI]

Xuan Wu

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Imbalanced Augmented Class Learning with Unlabeled Data by Label Confidence Propagation.

[BibT_eX]

[DOI]

Si-Yu Ding

Proceedings of the IEEE International Conference on Data Mining, 2018

A new R2 indicator for better hypervolume approximation.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2018

Feature-Induced Labeling Information Enrichment for Multi-Label Learning.

[BibT_eX]

[DOI]

Qian-Wen Zhang

Yun Zhong

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Multi-label Learning.

[BibT_eX]

[DOI]

Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Disambiguation-Free Partial Label Learning.

[BibT_eX]

[DOI]

Fei Yu

Cai-Zhi Tang

IEEE Trans. Knowl. Data Eng., 2017

Maximum margin partial label learning.

[BibT_eX]

[DOI]

Fei Yu

Mach. Learn., 2017

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

[BibT_eX]

[DOI]

Wang Zhan

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Binary Linear Compression for Multi-label Classification.

[BibT_eX]

[DOI]

Wen-Ji Zhou

Yang Yu

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Multi-label Learning with Label-Specific Features via Clustering Ensemble.

[BibT_eX]

[DOI]

Wang Zhan

Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

Confidence-Rated Discriminative Partial Label Learning.

[BibT_eX]

[DOI]

Cai-Zhi Tang

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Partial Label Learning via Feature-Aware Disambiguation.

[BibT_eX]

[DOI]

Bin-Bin Zhou

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Multi-Label Manifold Learning.

[BibT_eX]

[DOI]

Peng Hou

Xin Geng

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Lift: Multi-Label Learning with Label-Specific Features.

[BibT_eX]

[DOI]

Lei Wu

IEEE Trans. Pattern Anal. Mach. Intell., 2015

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

[BibT_eX]

[DOI]

Fei Yu

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Towards Class-Imbalance Aware Multi-Label Learning.

[BibT_eX]

[DOI]

Yu-Kun Li

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

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

[BibT_eX]

[DOI]

Yu-Kun Li

Xin Geng

Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

2014

A Review on Multi-Label Learning Algorithms.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2014

Disambiguation-Free Partial Label Learning.

[BibT_eX]

[DOI]

Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

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

[BibT_eX]

[DOI]

Yu-Kun Li

Proceedings of the PRICAI 2014: Trends in Artificial Intelligence, 2014

2013

Exploiting unlabeled data to enhance ensemble diversity.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2013

Multi-Label Classification with Unlabeled Data: An Inductive Approach.

[BibT_eX]

[DOI]

Le Wu

Proceedings of the Asian Conference on Machine Learning, 2013

2012

Introduction to the special issue on learning from multi-label data.

[BibT_eX]

[DOI]

Grigorios Tsoumakas

Mach. Learn., 2012

Multi-instance multi-label learning.

[BibT_eX]

[DOI]

Artif. Intell., 2012

2011

CoTrade: Confident Co-Training With Data Editing.

[BibT_eX]

[DOI]

IEEE Trans. Syst. Man Cybern. Part B, 2011

LIFT: Multi-Label Learning with Label-Specific Features.

[BibT_eX]

[DOI]

Proceedings of the IJCAI 2011, 2011

2010

Multi-label learning by exploiting label dependency.

[BibT_eX]

[DOI]

Kun Zhang

Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

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

[BibT_eX]

[DOI]

Proceedings of the 22nd IEEE International Conference on Tools with Artificial Intelligence, 2010

2009

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

[BibT_eX]

[DOI]

Neural Process. Lett., 2009

Feature selection for multi-label naive Bayes classification.

[BibT_eX]

[DOI]

José María Peña Sánchez

Víctor Robles

Inf. Sci., 2009

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

[BibT_eX]

[DOI]

Zhijian Wang

Neurocomputing, 2009

Classifier Ensemble with Unlabeled Data

[BibT_eX]

[DOI]

CoRR, 2009

Multi-instance clustering with applications to multi-instance prediction.

[BibT_eX]

[DOI]

Appl. Intell., 2009

2008

MIML: A Framework for Learning with Ambiguous Objects

[BibT_eX]

[DOI]

CoRR, 2008

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

[BibT_eX]

[DOI]

Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

2007

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

[BibT_eX]

[DOI]

Pattern Recognit., 2007

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

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2007

Multi-Label Learning by Instance Differentiation.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006

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

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2006

Adapting RBF Neural Networks to Multi-Instance Learning.

[BibT_eX]

[DOI]

Neural Process. Lett., 2006

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

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2005

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

[BibT_eX]

[DOI]

Proceedings of the 2005 IEEE International Conference on Granular Computing, 2005

2004

Improve Multi-Instance Neural Networks through Feature Selection.

[BibT_eX]

[DOI]

Neural Process. Lett., 2004

Ensembles of Multi-Instance Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Information Processing II, 2004

2003

A Novel Bag Generator for Image Database Retrieval With Multi-Instance Learning Techniques.

[BibT_eX]

[DOI]

Ke-Jia Chen

Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2003), 2003

Ensembles of Multi-instance Learners.

[BibT_eX]

[DOI]