| Expected reciprocal rank for graded relevance O Chapelle, D Metlzer, Y Zhang, P Grinspan Proceedings of the 18th ACM conference on Information and knowledge …, 2009 | 769 | 2009 |
| A dynamic bayesian network click model for web search ranking O Chapelle, Y Zhang Proceedings of the 18th international conference on World wide web, 1-10, 2009 | 519 | 2009 |
| Part-stacked cnn for fine-grained visual categorization S Huang, Z Xu, D Tao, Y Zhang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 245 | 2016 |
| Actional-Structural Graph Convolutional Networks for Skeleton-based Action Recognition M Li, S Chen, X Chen, Y Zhang, Y Wang, Q Tian Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 159 | 2019 |
| A machine learning-based framework to identify type 2 diabetes through electronic health records T Zheng, W Xie, L Xu, X He, Y Zhang, M You, G Yang, Y Chen International journal of medical informatics 97, 120-127, 2017 | 150 | 2017 |
| Deep feature for text-dependent speaker verification Y Liu, Y Qian, N Chen, T Fu, Y Zhang, K Yu Speech Communication 73, 1-13, 2015 | 147 | 2015 |
| Active Learning for Ranking through Expected Loss Optimization B Long, J Bian, O Chapelle, Y Zhang, Y Inagaki, Y Chang IEEE transactions on knowledge and data engineering 27 (5), 1180-1191, 2015 | 115 | 2015 |
| Active learning for ranking through expected loss optimization B Long, O Chapelle, Y Zhang, Y Chang, Z Zheng, B Tseng Proceedings of the 33rd international ACM SIGIR conference on Research and …, 2010 | 115* | 2010 |
| Multi-task learning for boosting with application to web search ranking O Chapelle, P Shivaswamy, S Vadrevu, K Weinberger, Y Zhang, B Tseng Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010 | 109 | 2010 |
| Identification of functional modules in protein complexes via hyperclique pattern discovery HUI XIONG, X HE, C Ding, Y Zhang, V Kumar, SR Holbrook | 87 | 2005 |
| Boosted multi-task learning O Chapelle, P Shivaswamy, S Vadrevu, K Weinberger, Y Zhang, B Tseng Machine learning 85 (1-2), 149-173, 2011 | 84 | 2011 |
| Maximizing expected model change for active learning in regression W Cai, Y Zhang, J Zhou 2013 IEEE 13th International Conference on Data Mining, 51-60, 2013 | 79 | 2013 |
| A time-series biclustering algorithm for revealing co-regulated genes Y Zhang, H Zha, CH Chu Information Technology: Coding and Computing, 2005. ITCC 2005. International …, 2005 | 79 | 2005 |
| Masking: A new perspective of noisy supervision B Han, J Yao, G Niu, M Zhou, I Tsang, Y Zhang, M Sugiyama Advances in Neural Information Processing Systems, 5836-5846, 2018 | 75 | 2018 |
| Augmenting Strong Supervision Using Web Data for Fine-grained Categorization Z Xu, S Huang, Y Zhang, D Tao Proceedings of the IEEE International Conference on Computer Vision, 2524-2532, 2015 | 71 | 2015 |
| Architectural style classification using multinomial latent logistic regression Z Xu, D Tao, Y Zhang, J Wu, AC Tsoi European Conference on Computer Vision, 600-615, 2014 | 65 | 2014 |
| Splice site prediction using support vector machines with a Bayes kernel Y Zhang, CH Chu, Y Chen, H Zha, X Ji Expert Systems with Applications 30 (1), 73-81, 2006 | 63 | 2006 |
| Joint optimization for consistent multiple graph matching J Yan, Y Tian, H Zha, X Yang, Y Zhang, S Chu Proceedings of the IEEE International Conference on Computer Vision, 1649-1656, 2013 | 60 | 2013 |
| Webly-supervised fine-grained visual categorization via deep domain adaptation Z Xu, S Huang, Y Zhang, D Tao IEEE transactions on pattern analysis and machine intelligence 40 (5), 1100-1113, 2018 | 59 | 2018 |
| Separating style and content for generalized style transfer Y Zhang, Y Zhang, W Cai Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 57 | 2018 |
Hongyuan Zha 査宏远School of Data Science, The Chinese University of Hong Kong, ShenzhenVerified email at cuhk.edu.cn
