Publications

2019|2018|2017|2016|2015|2014|2013|2012|2011|2010
2019
Conference Papers
Y. Zhang, W.-P. Fan, X. Wu, H. Chen, B.-Y. Li, M.-L. Zhang. CAFE: Adaptive VDI workload prediction with multi-grained features. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19), Honolulu, HI, 2019, in press.

B.-B. Jia, M.-L. Zhang. Multi-dimensional classification via kNN feature augmentation. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19), Honolulu, HI, 2019, in press.

J.-P. Fang, M.-L. Zhang. Partial multi-label learning via credible label elicitation. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19), Honolulu, HI, 2019, in press.

K. Su, D. Yu, Z. Xu, X. Geng and C. Wang. Multi-Person Pose Estimation with Enhanced Channel-wise and Spatial Information. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR’19), Long Beach, CA, 2019, in press.

C. Xu and X. Geng, Hierarchical Classification based on Label Distribution Learning. In: Proceedings of the 33rd AAAI C, onference on Artificial Intelligence (AAAI'19), Honolulu, HI, 2019, in press.

K. Su and X. Geng, Soft Facial Landmark Detection by Label Distribution Learning. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19), Honolulu, HI, 2019, in press.

J. Wang and X. Geng, Theoretical Analysis of Label Distribution Learning. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19), Honolulu, HI, 2019, in press.

N. Xu, J. Lv and X. Geng, Partial Label Learning via Label Enhancement. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19), Honolulu, HI, 2019, in press.
2018
Journal Articles
D. Zhou, Z. Zhang, M.-L. Zhang, Y. He. Weakly supervised POS tagging without disambiguation. ACM Transactions on Asian and Low-Resource Language Information Processing, 2018, 17(4): Article 35.

Deyu Zhou, Lei Miao, Yulan He. Position-aware deep multi-task learning for drug–drug interaction extraction, Artificial Intelligence In Medicine, Accepted, 2018.
Conference Papers
Yang Yang , Deyu Zhou and Yulan He, An Interpretable Neural Network with Topical Information for Relevant Emotion Ranking, In: Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31-November 4, 2018.

J. Wang, M.-L. Zhang. Towards mitigating the class-imbalance problem for partial label learning. In: Proceedings of the 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'18), London, UK, 2018, 2427-2436.

S.-Y. Ding, X.-Y. Liu, M.-L. Zhang. Imbalanced augmented class learning with unlabeled data by label confidence propagation. In: Proceedings of the 18th IEEE International Conference on Data Mining (ICDM'18), Singapore, in press.

N. Xu, A. Tao and X. Geng. Label Enhancement for Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'18), Stockholm, Sweden, 2018, 2926-2932.

K. Wang and X. Geng. Binary Coding based Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'18), Stockholm, Sweden, 2018, 2783-2789.

C.-L. Peng, A. Tao and X. Geng. Label Embedding Based on Multi-Scale Locality Preservation. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'18), Stockholm, Sweden, 2018, 2623-2629.

Bin-Bin Gao, Hong-Yu Zhou, Jianxin Wu, and Xin Geng. Age Estimation Using Expectation of Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'18), Stockholm, Sweden, 2018, 712-718.

X. Wu, M.-L. Zhang. Towards enabling binary decomposition for partial label learning. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18), Stockholm, Sweden, in press.

Q.-W. Zhang, Y. Zhong, M.-L. Zhang. Feature-induced labeling information enrichment for multi-label learning. In: Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI'18), New Orleans, LA, in press.

Deyu Zhou, Yang Yang and Yulan He, Relevant Emotion Ranking from Text Constrained with Emotion Relationships, In: The North American Chapter of the Association for Computational Linguistics(NAACL 2018), New Orleans, Louisiana, June 1-6, 2018.

Deyu Zhou, Linsen Guo, Yulan He, Neural Storyline Extraction Model for Storyline Generation from News Articles, In: The North American Chapter of the Association for Computational Linguistics(NAACL 2018), New Orleans, Louisiana, June 1-6, 2018.
2017
Journal Articles
M.-L. Zhang, F. Yu, C.-Z. Tang. Disambiguation-free partial label learning. IEEE Transactions on Knowledge and Data Engineering, 2017, 29(10): 2155-2167.

F. Yu, M.-L. Zhang. Maximum margin partial label learning. Machine Learning, 2017, 106(4): 573-593.

B.-B. Gao, C. Xing, C.-W. Xie, J. Wu, and X. Geng. Deep Label Distribution Learning with Label Ambiguity. IEEE Transactions on Image Processing (IEEE TIP), 2017, in press.

Z. He, X. Li, Z. Zhang, F. Wu, X. Geng, Y. Zhang, M.-H Yang, and Y. Zhuang. Data-Dependent Label Distribution Learning for Age Estimation, IEEE Transactions on Image Processing (IEEE TIP), 2017, in press.
Conference Papers
Hui Xue, Yu Song, Haiming Xu. Multiple Indefinite Kernel Learning for Feature Selection. International Joint Conference on Artificial Intelligence (IJCAI),2017.

W.-J. Zhou, Y. Yu, M.-L. Zhang. Binary linear compression for multi-label classification. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17), Melbourne, Australia, 2017, 3546-3552.

Z. Huo and X. Geng. Ordinal Zero-Shot Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'17), Melbourne, Australia, 2017, in press.

Y. Ren and X. Geng. Sense Beauty by Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'17), Melbourne, Australia, 2017, in press.

W. Zhan, M.-L. Zhang. Inductive semi-supervised multi-label learning with co-training. In: Proceedings of the 23rd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'17), Halifax, Canada, 2017, 1305-1314.

X. Geng and M. Ling. Soft Video Parsing by Label Distribution Learning. In: Proceedings of the 31th AAAI Conference on Artificial Intelligence (AAAI’17), San Francisco, CA, 2017, 1331-1337.

Haiming Xu, Hui Xue, Xiaohong Chen, Yunyun Wang. Solving indefinite kernel support vector machine with difference of convex functions programming. Proceedings of 31th AAAI Conference on Artificial Intelligence (AAAI)，San Francisco，California，USA，2017.

P. Hou, X. Geng, Z. Huo, and J-Q Lv. Semi-supervised Adaptive Label Distribution Learning for Facial Age Estimation. In: Proceedings of the 31th AAAI Conference on Artificial Intelligence (AAAI’17), San Francisco, CA, 2017, 2015-2021.

C.-Z. Tang, M.-L. Zhang. Confidence-rated discriminative partial label learning. In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17), San Francisco, CA, 2017, 2611-2617.

Deyu Zhou, Xuan Zhang, Yulan He, Event extraction from Twitter using Non-Parametric Bayesian Mixture Model with Word Embeddings, In: Proceedings of the 2017 Conference on The European Chapter of the Association for Computational Linguistics(EACL 2017), Valencia, April 3-7, 2017.

Haiming Xu, Hui Xue, Xiaohong Chen, Yunyun Wang. Solving indefinite kernel support vector machine with difference of convex functions programming. Proceedings of 31th AAAI Conference on Artificial Intelligence (AAAI)，San Francisco，California，USA，2017.
2016
Journal Articles
X. Geng. Label Distribution Learning. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2016, in press.

Z. He, X. Li, Z. Zhang, F. Wu, X. Geng, Y. Zhang, M.-H Yang, and Y. Zhuang. Data-Dependent Label Distribution Learning for Age Estimation, IEEE Transactions on Image Processing (IEEE TIP), 2016, in press.

H. Zheng and X. Geng. A Multi-Task Model for Simultaneous Face Identification and Facial Expression Recognition. Neurocomputing, 2016, vol. 171: 515-523.

Deyu Zhou, Liangyu Chen, Xuan Zhang, Yulan He, Unsupervised Event Exploration from Social Text Streams, Intelligent Data Analysis, Accepted, 2016.

Qing Tian, Hui Xue, Lishan Qiao. Human age estimation by considering both the ordinality and similarity of ages. Neural Processing Letters, 43: 505-521, 2016.

Mingxia Liu, Daoqiang Zhang, Songcan Chen, Hui Xue. Joint binary classifier learning for ECOC-based multi-class classification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(11): 2335-2341, 2016.
Conference Papers
Deyu Zhou, Xuan Zhang, Yin Zhou, Quan Zhao, Xin Geng, Emotion Distribution Learning from Text s, In: Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing(EMNLP 2016), Austin, Texas, USA, November 1–5, 2016.

X. Yang, X. Geng and D.-Y. Zhou. Sparsity Conditional Energy Label Distribution Learning for Age Estimation. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'16), New York City, NY, 2016, 2259-2265.

C. Xing, X. Geng and Hui Xue. Logistic Boosting Regression for Label Distribution Learning. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR’16), Las Vegas, NV, 2016, 4489-4497.

P. Hou, X. Geng and M.-L. Zhang. Multi-Label Manifold Learning. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16), Phoenix, AZ, 2016, 1680-1686.

M.-L. Zhang, B.-B. Zhou, X.-Y. Liu. Partial label learning via feature-aware disambiguation. In: Proceedings of the 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'16), San Francisco, CA, 2016, 1335-1344.

P. Hou, X. Geng, M.-L. Zhang. Multi-label manifold learning. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16), Phoenix, AZ, 2016, 1680-1686.

Deyu Zhou, Tianmeng Gao, Yulan He, Jointly Event Extraction and Visualization on Twitter via Prob abilistic Modelling, In: Proceedings of the 54th Annual Meeting of the Association for Computation al Linguistics (ACL 2016), In press.

Deyu Zhou, Haiyang Xu, Xinyu Dai, Yulan He, Unsupervised Storyline Extraction from News Article s, In: Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), In press.

D. Zhou, Y. Zhou, X. Zhang, Q. Zhao and X. Geng. Emotion Distribution Learning from Texts. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP'16), Austin, TX, 2016, 638-647.

Fa Zheng, Hui Xue, Xiaohong Chen, Yunyun Wang. Maximum margin tree error correcting output codes. Proceedings of 14th Pacific Rim International Conference on Artificial Intelligence (PRICAI), LNAI 9810, 681-691, Phuket, Thailand, 2016.
2015
Journal Articles
Min-Ling Zhang, Lei Wu. LIFT: Multi-label learning with label-specific features. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 2015, 37(1): 107-120.

Zhaoxiang Zhang, Mo Wang, Xin Geng. Crowd Counting in Public Video Surveillance by Label Distribution Learning. Neurocomputing, 2015, vol. 166: 151-163.

Deyu Zhou, Dayou Zhong. A semi-supervised learning framework for biomedical event extraction based on hidden topics, Artificial Intelligence In Medicine, Volume 64, No.1, pp. 51-58, 2015
Conference Papers
F. Yu, M.-L. Zhang. Maximum margin partial label learning. In: Proceedings of the 7th Asian Conference on Machine Learning (ACML'15), Hong Kong, China, 2015, 96-111.

Xin Geng and Peng Hou. Pre-release Prediction of Crowd Opinion on Movies by Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'15), Buenos Aires, Argentina, 2015, in press.

Min-Ling Zhang, Fei Yu. Solving the Partial Label Learning Problem: An Instance-based Approach, In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'15), Buenos Aires, Argentina, 2015, in press.

Min-Ling Zhang, Yu-Kun Li, Xu-Ying Liu. Towards Class-imbalance Aware Multi-label Learning, In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'15), Buenos Aires, Argentina, 2015, in press.

Y.-K. Li, M.-L. Zhang and X. Geng. Leveraging Implicit Relative Labeling-importance Information for Effective Multi-label Learning. In: Proceedings of the 15th IEEE International Conference on Data Mining (ICDM'15), Atlantic City, NJ, 2015, 251-260.

Ying Zhou, Hui Xue, Xin Geng, Emotion Distribution Recognition from Facial Expressions. In: Proceedings of the 23rd ACM International Conference on Multimedia (ACM MM'15),Brisbane, Australia, 2015, in press.

Deyu Zhou, Haiyang Xu, Yulan He. An Unsupervised Bayesian Modelling Approach for Storyline De tection on News Articles, In: Proceedings of the 2015 Joint Conference on Empirical Methods in Nat ural Language Processing and Computational Natural Language Learning, (EMNLP 2015), Lisbon, Portugal, September 17–21, 2015 .

Deyu Zhou, Liangyu Chen, Yulan He. An Unsupervised Framework of Exploring Events on Twitter: Filtering, Extraction and Categorization, In: Proceedings of the Twenty-Ninth AAAI Conference on A rtificial Intelligence (AAAI 2015), Austin, Texas, USA, January 25 – 30, 2015 .
2014
Book Chapter
X. Geng, Facial Age Estimation: A Data Representation Perspective. Yun Fu ed., Human-Centered Social Media Analytics, Springer, NY, USA, 2014.
Journal Articles
Min-Ling Zhang, Zhi-Hua Zhou. A review on multi-label learning algorithms. IEEE Transactions on Knowledge and Data Engineering, 2014, 26(8): 1819-1837.

Hui Xue, Songcan Chen. Discriminality-driven regularization framework for indefinite kernel machine. Neurocomputing, 133: 209-221, 2014

Deyu Zhou, Dayou. Zhong and Yulan He. Event Trigger Identification for Biomedical Events Extraction using Domain Knowledge, Bioinformatics, Vol: 30 No: 11 pp 1587-1594
Conference Papers
X. Geng and Y. Xia. Head Pose Estimation Based on Multivariate Label Distribution. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR'14), Columbus, OH, 2014, pp. 1837-1842.

X. Geng and L. Luo. Multilabel Ranking with Inconsistent Rankers. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR'14), Columbus, OH, 2014, pp. 3742-3747.

X. Geng, Q. Wang, and Y. Xia. Facial Age Estimation by Adaptive Label Distribution Learning. In: Proceedings of the 22nd International Conference on Pattern Recognition (ICPR'14, Oral), Stockholm, Sweden, 2014, in press.

Deyu Zhou, Liangyu Chen, and Yulan He, A Simple Bayesian Modelling Approach to Event Extraction from Twitter, the 52nd Annual Meeting of the Association for Computational Linguistics (ACL), 2014, USA.

Min-Ling Zhang. Disambiguation-free partial label learning. In: Proceedings of the 14th SIAM International Conference on Data Mining (SDM'14), Philadelphia, PA, 2014, 37-45.

X.-Y. Liu, and Q.-Q. Li. Learning from combination of data chunks for multi-class imbalanced data. In: Proceedings of 2014 International Joint Conference on Neural Networks (IJCNN’14), Beijing, China, 2014.7.6-11, accepted, 2014.

Dayin Zhang, Hui Xue. Lp-norm multiple kernel learning with diversity of classes. Pacific Rim Knowledge Acquisition Workshop (PKAW), 38-47, Gold Coast, Australia, 2014.
2013
Journal Articles
Min-Ling Zhang, Zhi-Hua Zhou. Exploiting unlabeled data to enhance ensemble diversity. Data Mining and Knowledge Discovery, 2013, 26(1): 98-129.

X. Geng, C. Yin, and Z.-H. Zhou. Facial Age Estimation by Learning from Label Distributions. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2013, 35(10): 2401-2412.

Hui Xue, Songcan Chen. Orthogonality-based label correction in multi-class classification. Electronics Letters, 49(12): 754-755, 2013
Conference Papers
Lei Wu, Min-Ling Zhang. Multi-label classification with unlabeled data: An inductive approach. In: Proceedings of the 5th Asian Conference on Machine Learning (ACML'13), Canberra, Australia, 2013, 197-212.

X.-Y. Liu, Q.-Q. Li and Z.-H. Zhou. Learning imbalanced multi-class data with optimal dichotomy weights. In: Proceedings of the 13th IEEE International Conference on Data Mining (ICDM'13), Dallas, TX, 2013.12.7-10, pp. 478-487, 2013.

Z.-C. Dai, A. Sun, and X.-Y. Liu. Crest: Cluster-based Representation Enrichment for Short Text Classification. In: Proceedings of the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’13), Gold Coast, Australia, 2013.4.14-17, 256-267, 2013.
2012
Conference Papers
Hui Xue, Songcan Chen, Jijian Huang. Discriminative indefinite kernel classifier from pairwise constraints and unlabeled data. In: Proceedings of the 21st International Conference on Pattern Recognition (ICPR), 497-500, Tsukuba, Japan, 2012

Hui Xue, Songcan Chen, Jie Liu, Jijian Huang. A novel classification method with cross-view constraints. In: Proceedings of the 1st International Workshop on Learning with Weak Supervision (LAWS) in conjunction with the 4th Asian Conference on Machine Learning (ACML), 17-29, Singapore, 2012

Jijian Huang, Hui Xue, Yuqing Zhai. Semi-supervised discriminatively regularized classifier with pairwise constraints. In: Proceedings of the 12th Pacific Rim International Conference on Artificial Intelligence (PRICAI), LNAI 7458, 112-123, Kuching, Sarawak, Malaysia, 2012
2011
Journal Articles
X. Geng, K. Smith-Miles, Z.-H. Zhou, and L. Wang. Face Image Modeling by Multilinear Subspace Analysis with Missing Values. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics (IEEE TSMC-B), 2011, 41(3): 881 - 892.

Min-Ling Zhang, Zhi-Hua Zhou. CoTrade: Confident co-training with data editing. IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics, 2011, 41(6): 1612-1626.

Hui Xue, Songcan Chen, Qiang Yang. Structural regularized support vector machine: a framework for structural large margin classifier. IEEE Transactions on Neural Networks, 22(4): 573-587, 2011

Hui Xue, Songcan Chen. Glocalization pursuit support vector machine. Neural Computing and Applications, 20(7): 1043-1053, 2011

Deyu Zhou and Yulan He. Biomedical Events Extraction using the Hidden Vector State Model, Artificial Intelligence in Medicine, Vol. 53, No. 3, pp. 205-13, 2011.

Yulan He and Deyu Zhou. Self-Training from Labeled Features for Sentiment Analysis, Information Processing & Management, Vol. 47, No. 4, pp. 606-616, 2011.
Conference Papers
Deyu Zhou and Yulan He. A Novel Framework of Training Hidden Markov Support Vector Machines from Lightly-Annotated Data, The 20th ACM Conference on Information and Knowledge Management (CIKM) Glasgow, Scotland, Oct. 2011.

Deyu Zhou and Yulan He. Learning Conditional Random Fields from Unaligned Data for Natural Language Understanding, The 33rd European Conference on Information Retrieval (ECIR), Dublin, Ireland, 2011.

Min-Ling Zhang. LIFT: Multi-label learning with label-specific features. In: Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI'11), Barcelona, Spain, 2011, 1609-1614.
2010
Journal Articles
L. Wang, X. Geng, J. Bezdek, C. Leckie, K. Ramamohanarao, Enhanced Visual Analysis for Cluster Tendency Assessment and Data Partitioning. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2010, 22(10): 1401-1414.

Z.-H. Zhou and X.-Y. Liu. On multi-class cost-sensitive learning. Computational Intelligence, 26(3):232-257, 2010.

X. Geng, K. Smith-Miles, L. Wang, M. Li, Q. Wu, Context-Aware Fusion: A Case Study on Fusion of Gait and Face for Human Identification in Video. Pattern Recognition (PRJ), 2010, 43(10): 3660-3673.
Conference Papers
X. Geng, K. Smith-Miles, Z.-H. Zhou. Facial Age Estimation by Learning from Label Distributions. In: Proceedings of the 24th AAAI Conference on Artificial Intelligence (AAAI'10), Atlanta, GA, 2010, pp. 451-456.

X.-Y. Liu and Z.-H. Zhou. Learning with cost intervals. In: Proceedings of the 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'10), Washington, DC, 2010.7.25-28, pp. 403-412, 2010.

Min-Ling Zhang, Zhi-Hua Zhou. Exploiting unlabeled data to enhance ensemble diversity. In: Proceedings of the 10th IEEE International Conference on Data Mining (ICDM’10), Sydney, Australia, 2010, 619-628.

Min-Ling Zhang, Kun Zhang. Multi-label learning by exploiting label dependency. In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’10), Washington D.C., 2010, 999-1007.