H.-J. Ye, D.-C. Zhan, N. Li, Y. Jiang. Learning Multiple Local Metrics: Global Consideration Helps. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019, in press.
Han-Jia Ye, De-Chuan Zhan, Yuan Jiang. Fast Generalization Rates for Distance Metric Learning. Machine Learning, 2019, 108(2): 267-295.
Shao-Yuan Li, Yuan Jiang, Nitesh Chawla, and Zhi-Hua Zhou. Multi-label learning from crowds. IEEE Transactions on Knowledge and Data Engineering, 2019, 31(7): 1369-1382.
Han-Jia Ye, De-Chuan Zhan, Yuan Jiang, Zhi-Hua Zhou. What Makes Objects Similar: A Unified Multi-Metric Learning Approach. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019, 41(5): 1257-1270.
Ju-Hua Hu, De-Chuan Zhan, Xintao Wu, Yuan Jiang, and Zhi-Hua Zhou. Pairwised Specific Distance Learning from Physical Linkages. ACM Transactions on Knowledge Discovery from Data, 2015, 9(3):Article 20.
Lei Yuan, Alexander Woodard, Shuiwang Ji, Yuan Jiang, Zhi-Hua Zhou, Sudhir Kumar, and Jieping Ye. Learning sparse representations for fruit-fly gene expression pattern image annotation and retrieval. BMC Bioinformatics, 2012, 13: 107.
Yuan Jiang, Ming Li, Zhi-Hua Zhou. Software defect detection with ROCUS. Journal of Computer Science and Technology, 2011, 26(2): 328-342.
Yuan Jiang, Ming Li, Zhi-Hua Zhou. Mining extremely small data sets with application to software reuse. Software: Practice and Experience, 2009, 39(4): 423-440.
Yuan Jiang, Ke-Jia Chen, Zhi-Hua Zhou. SOM ensemble-based image segmentation. Neural Processing Letters, 2004, 20(3): 171-178.
Yong Wang, Yuan Jiang, Yi Wu, Zhi-Hua Zhou. Spectral clustering on multiple manifolds. IEEE Transactions on Neural Networks, 2011, 22(7): 1149-1161.
Zhi-Hua. Zhou and Yuan. Jiang. NeC4.5: neural ensemble based C4.5. IEEE Transactions on Knowledge and Data Engineering, 2004, 16(6): 770-773.
Zhi-Hua Zhou, Yuan Jiang. Medical diagnosis with C4.5 rule preceded by artificial neural network ensemble. IEEE Transactions on Information Technology in Biomedicine, 2003, 7(1): 37-42.
胡菊花, 姜远, 周志华. 一种基于教学模型的协同训练方法. 计算机研究与发展, 2013, 50(11): 2262-2268.
佘俏俏, 俞扬, 姜远, 周志华. 一种基于标记传播的大规模图像分类方法. 计算机研究与发展, 2012, 49(11): 2289-2295.
姜远, 黎铭, 周志华. 一种基于半监督学习的多模态Web查询精化方法. 计算机学报, 2009, 32(10), 2099-2106.
姜远, 佘俏俏, 黎铭, 周志华. 一种直推式多标记文档分类方法. 计算机研究与发展, 2008, 45(11): 1817-1823.
姜远, 周志华. 基于词频分类器集成的文本分类方法. 计算机研究与发展, 2006, 43(10): 1681-1687.
孔祥南, 黎铭, 姜远, 周志华. 一种针对弱标记的直推式多标记分类方法. 计算机研究与发展, 2010, 47(8): 1392-1399.
薛晓冰, 韩洁凌, 姜远, 周志华. 基于多示例学习技术的Web目录页面链接推荐. 计算机研究与发展, 2007, 44(3): 406-411.
眭俊明, 姜远, 周志华. 基于频繁项集挖掘的贝叶斯分类算法. 计算机研究与发展, 2007, 44(8): 1293-1300.
Y. Yang, K.-T. Wang, D.-C. Zhan, H. Xiong, Y. Jiang. Comprehensive Semi-Supervised Multi-Modal Learning. In: Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI’19), Macao, China, 2019.
Z.-Y. Zhang, P. Zhao, Y. Jiang, and Z.-H. Zhou. Learning from incomplete and inaccurate supervision. In: Proceedings of the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’19), Anchorage, AL, 2019.
Y. Yang, D.-W. Zhou, D.-C. Zhan, H. Xiong, Y. Jiang. Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability. In: Proceedings of the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’19), Anchorage, AL, 2019.
Y. Yang, Y.-F. Wu, D.-C. Zhan, Z.-B. Liu, Y. Jiang. Deep Robust Unsupervised Multi-Modal Network. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI’19), Honolulu, HI, 2019.
X.-R. Sheng, D.-C. Zhan, S. Lu, Y. Jiang. Multi-View Anomaly Detection: Neighborhood in Locality Matters. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI’19), Honolulu, HI, 2019.
Y.-F. Wu, D.-C. Zhan, Y. Jiang. DMTMV: A Unified Learning Framework for Deep Multi-Task Multi-View Learning. In: Proceedings of the 2018 IEEE International Conference on Big Knowledge (ICBK’18), Singapore, 2018.
H.-J. Ye, D.-C. Zhan, Y. Jiang, Z.-H. Zhou. Rectify Heterogeneous Model with Semantic Mapping. In: Proceedings of the 35th International Conference on Machine Learning (ICML’18), Stockholm, Sweden, 2018.
Y. Yang, Y.-F. Wu, D.-C. Zhan, Z.-B. Liu, Y. Jiang. Complex Object Classification: A Multi-Modal Multi-Instance Multi-Label Deep Network with Optimal Transport. In: Proceedings of the Annual Conference on ACM SIGKDD (KDD’18), London, UK, 2018.
Y. Yang, D.-C. Zhan, X.-R. Sheng, Y. Jiang. Semi-Supervised Multi-Modal Learning with Incomplete Modalities. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI’18), Stockholm, Sweden, 2018.
C. Liu, P. Zhao, S.-J. Huang, Y. Jiang, and Z.-H. Zhou. Dual set multi-label learning. In: Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI’18) , New Orleans, LA, 2018.
Y. Yang, Y.-F. Wu, D.-C. Zhan, Y. Jiang. Multi-Network User Identification via Graph-Aware Embedding. In: Proceedings of the 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’18) , Melbourne, Australia, 2018.
Y. Yang, D.-C. Zhan, Y. Fan, Y. Jiang. Instance Specific Discriminative Modal Pursuit: A Serialized Approach. In: Proceedings of the 9th Asian Conference on Machine Learning (ACML’17), Seoul, Korea, 2017.
H.-J. Ye, D.-C. Zhan, X.-M. Si, Y. Jiang. Learning Mahalanobis Distance Metric: Considering Instance Disturbance Helps. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI’17), Melbourne, Australia, 2017.
Y. Yang, D.-C. Zhan, X.-Y. Guo, Y. Jiang. Modal Consistency based Pre-trained Multi-Model Reuse. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI’17), Melbourne, Australia, 2017.
Y. Zhang, Y. Jiang. Multimodal Linear Discriminant Analysis via Structural Sparsity. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI’17), Melbourne, Australia, 2017.
W. Wang, X.-Y. Guo, S.-Y. Li, Y. Jiang, and Z.-H. Zhou. Obtaining high-quality label by distinguishing between easy and hard items in crowdsourcing. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI’17), Melbourne, Australia, 2017.
P. Zhao, Y. Jiang, and Z.-H. Zhou. Multi-view matrix completion for clustering with side information. In: Proceedings of the 21st Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’17), LNAI, Jeju, Korea, 2017.
Y. Yang, D.-C. Zhan, Y. Fan, Y. Jiang, and Z.-H. Zhou. Deep learning for fixed model reuse. In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI’17), San Francisco, CA, 2017.
H.-J. Ye, D.-C. Zhan, X.-M. Si, Y. Jiang and Z.-H. Zhou. What makes objects similar: a unified multi-metric learning approach. In: Proceedings of 30th Advances in Neural Information Processing Systems 29 (NIPS’16), Barcelona, Spain, 2016. P1235-1243
H.-J. Ye, D.-C. Zhan, X.-L. Li, Z.-C. Huang and Y. Jiang. College student scholarships and subsidies granting: a multi-modal multi-label approach. In: Proceedings of the 16th IEEE International Conference on Data Mining (ICDM’16), Barcelona, Spain, 2016.
H.-J. Ye, D.-C. Zhan, X.-M. Si and Y. Jiang. Learning feature aware metric. In: Proceedings of the 8th Asian Conference on Machine Learning (ACML’16), New Zealand, 2016, P286-301
Y. Yang, D.-C. Zhan, Y. Jiang. Learning by Actively Querying Strong Modal Features. In: Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI’16), New York, USA, 2016.
H.-J. Ye, D.-C. Zhan, and Y. Jiang. Instance specific metric subspace learning: A bayesian approach. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI’16), Phoenix, AZ, 2016.
H.-J. Ye, D.-C. Zhan, Y. Miao, Y. Jiang, and Z.-H. Zhou. Rank consistency based multi-view learning: A privacy-preserving approach. In: Proceedings of the 24th ACM International Conference on Information and Knowledge Management (CIKM’15), Melbourne, Australia, 2015, 991-1000.
Nan Li, Yuan Jiang, Zhi-Hua Zhou. Multi-Label Selective Ensemble. In: Proceedings of the 12th International Workshop, MCS 2015, Günzburg, Germany, 2015, 76-88.
Yang Yang, Han-Jia Ye, De-Chuan Zhan, Yuan Jiang. Auxiliary Information Regularized Machine for Multiple Modality Feature Learning. In: Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI’15), Buenos Aires, Argentina, 2015, 1033-1039.
Shao-Yuan Li, Yuan Jiang, and Zhi-Hua Zhou. Partial multi-view clustering. In: Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI‘14), Quebec, Canada, 2014, 1968-1974.
Yue Zhu, Jianxin Wu, Yuan Jiang, and Zhi-Hua Zhou. Learning with Augmented Multi-Instance View. In: Proceedings of the 6st Asian Conference on Machine Learning (ACML’14), Nha Trang, Vietnam, 2014, JMLR: W&CP.
Shaowu Liu, Truyen Tran, Gang Li, and Yuan Jiang. Ordinal Random Fields for Recommender Systems. In: Proceedings of the 6st Asian Conference on Machine Learning (ACML’14), Nha Trang, Vietnam, 2014, JMLR: W&CP.
Shu-Jun Yang, Yuan Jiang, and Zhi-Hua Zhou. Multi-instance multi-label learning with weak label. In: Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI’13), Beijing, China, 2013,1862-1868.
Yu-Feng Li, Ju-Hua Hu, Yuan Jiang, and Zhi-Hua Zhou. Towards discovering what patterns trigger what labels. In: Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI’12), Toronto, Canada, 2012,1012-1018.
Xin-Shun Xu, Yuan Jiang, Xiangyang Xue and Zhi-Hua Zhou. Semi-supervised multi-instance multi-label learning for video annotation task. In: Proceedings of the 20th ACM International Conference on Multimedia (MM’12), Nara, Japan, 2012, 737-740.
Quannan Li, Xinggang Wang, Wei Wang, Yuan Jiang, Zhi-Hua Zhou, and Zhuowen Tu. Disagreement-based multi-system tracking. In: Proceedings of the ACCV Workshop on Detection and Tracking in Challenging Environments (DTCE’12), Daejeon, Korea, 2012, 320-334.
Xin-Shun Xu, Yuan Jiang, Peng Liang, Xiangyang Xue, Zhi-Hua Zhou. Ensemble approach based on conditional random field for multi-label image and video annotation. In: Proceedings of the 19th ACM International Conference on Multimedia (MM’11), Scottsdale, AZ, 2011.
Yong Wang, Yuan Jiang, Yi Wu, Zhi-Hua Zhou. Local and structural consistency for multi-manifold clustering. In: Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI’11), Barcelona, Spain, 2011, 1559-1564.
Yong Wang, Yuan Jiang, Yi Wu, Zhi-Hua Zhou. Localized K-flats. In: Proceedings of the 25th AAAI Conference on Artificial Intelligence (AAAI’11), San Francisco, CA, 2011, 525-530.
Yong Wang, Yuan Jiang, Yi Wu, Zhi-Hua Zhou. Multi-manifold clustering. In: Proceedings of the 11th Pacific Rim International Conference on Artificial Intelligence (PRICAI’10), Daegu, Korea, LNAI 6230, Zhang B-T, Orgun M A, eds. Berlin: Springer, 2010, 280-291. (”Best Paper Award”)
Li-Ping Liu, Yuan Jiang, Zhi-Hua Zhou. Least square incremental linear discriminant analysis. In: Proceedings of the 9th IEEE International Conference on Data Mining (ICDM’09), Miami, FL, 2009, 298-306.
Zhi-Hua Zhou, Michael Ng, Qiao-Qiao She, Yuan Jiang. Budget semi-supervised learning. In: Proceedings of the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’09) (Bangkok, Thailand), LNAI 5476, Theeramunkong T, Kijsirikul B, Cercone N, Ho T-B, eds. Berlin: Springer, 2009, 588-595.
Li-Ping Liu, Yang Yu, Yuan Jiang, Zhi-Hua Zhou. TEFE: A time-efficient approach to feature extraction. In: Proceedings of the 8th IEEE International Conference on Data Mining (ICDM’08), Pisa, Italy, 2008, 423-432.
Yuan Jiang, Ming Li, Zhi-Hua Zhou. Generation of comprehensible hypotheses from gene expression data. In: Li J Y, Yang Q, Tan A H, eds. Lecture Notes in Bioinformatics 3916 (BioDM’06) (Proceedings of the International Workshop on Data Mining for Biomedical Application, in conjunction with PAKDD’06, Singapore, April.2006), Berlin: Springer, 2006, 116-123.
Yuan Jiang, Jin-Jiang Ling, Gang Li, Honghua Dai, Zhi-Hua Zhou. Dependency bagging. In: Slezak D, Yao J T, Peters J F, Ziarko W, Hu X, eds. Lecture Notes in Artificial Intelligence 3641 (RSFDGrC’05) (Proceedings of the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, Regina, Canada, Sept.2005), Berlin: Springer, 2005, 491-500.
Yuan Jiang, Zhi-Hua Zhou. Editing Training Data for kNN Classifiers with Neural Network Ensemble. In: Yin F, Wang J, and Guo C eds. Lecture Notes in Computer Science 3173 (ISNN’04) (Proceedings of the 1st International Symposium on Neural Networks, Dalian, China, Aug. 2004), Berlin: Springer-Verlag, 2004, 356-361.
Zhi-Hua Zhou, Xiao-Bing Xue, Yuan Jiang. Locating regions of interest in CBIR with multi-instance learning techniques. In: Zhang S, Jarvis R, eds. Lecture Notes in Artificial Intelligence 3809 (AJCAI’05) (Proceedings of the 18th Australian Joint Conference on Artificial Intelligence, Sydney, Australia, Dec.2005), Berlin: Springer, 2005, 92-101.
Zhi-Hua Zhou, Ke-Jia Chen, Yuan Jiang. Exploiting Unlabeled Data in Content-Based Image Retrieval. In: Boulicaut J F, Esposito F, Giannotti F, Pedreschi D eds. Lecture Notes in Artificial Intelligence 3201 (ECML’04) (Proceedings of the 15th European Conference on Machine Learning, Pisa, Italy, Sept.2004), Berlin: Springer-Verlag, 2004, 525-536.
Yuan Jiang, Ke-Jia Chen, Zhi-Hua Zhou. SOM-based image segmentation. In: Wang G, Liu Q, Yao Y, Skowron A eds. Lecture Notes in Artificial Intelligence 2639 (RSFDGrC’03) (Proceedings of the 9th International Conference on Rough Sets, Fuzzy Sets, Data mining and Granular Computing, Chongqing, China, Aug. 2003), Berlin: Springer-Verlag, 2003, 640-643.
Yuan Jiang, Zhi-Hua Zhou, Morshed U. Chowdhury. Image retrieval based on the combination of color and keyword. In: Proceedings of the International Conference on Computer Science, Software Engineering, Information Technology, e-Business, and Applications (CSITeA’03, Rio de Janeiro, Brazil, June. 2003), Cary, NC: ISCA, 2003, 450-453.
Yuan Jiang, Zhi-Hua Zhou, Zhao-Qian Chen. Rule learning based on neural network ensemble. In: Proceedings of the International Joint Conference on Neural Networks (IJCNN’02) (Honolulu, HI, May. 2002), Piscataway, NJ: IEEE, 2002, vol.2, 1416-1420.
Zhi-Hua Zhou, Yuan Jiang, Xu-Ri Yin, Shi-Fu Chen. The application of visualization and neural network techniques in a power transformer condition monitoring system. In: Hendtlass T, Ali M eds. Lecture Notes in Artificial Intelligence 2358 (IEA/AIE’02) (Developments in Applied Artificial Intelligence, Proceedings of the 15th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Cairns, Australia, June. 2002), Berlin: Springer-Verlag, 2002, 325-334.
Zhi-Hua Zhou, Jian-Xin Wu, Yuan Jiang, Shi-Fu Chen. Genetic algorithm based selective neural network ensemble. In: Proceedings of the 17th International Joint Conference on Artificial Intelligence (Seattle, WA, July. 2001), San Francisco, CA: Morgan Kaufmann, 2001, vol.2, 797-802.
Yuan Jiang, Zhi-Hua Zhou, Chen Shifu. Visualization in power transformer state detection expert system. In: Proceedings of the Pacific-Asia International Conference on Microcomputer Application, 2000, 223-225.