Ya Zhang (张娅) , Ph.D

Bio

Ya Zhang is currently a Professor in Cooperative Medianet Innovation Center, Shanghai Jiao Tong University, and chief AI scientist of State Key Laboratory of UHD video and audio production and presentation. Her research interest is mainly on machine learning with applications to multimedia and healthcare. Dr. Zhang holds a PhD degree in Information Sciences and Technology from Pennsylvania State University and a Bachelor’s degree from Tsinghua University in China. Before joining Shanghai Jiao Tong University, Dr. Zhang was a research manager at Yahoo! Labs, where she leaded a R&D team of researchers with strong background in data mining and machine learning to improve the web search quality of Yahoo international markets. Prior to joining Yahoo, Dr. Zhang was an assistant professor at University of Kansas with research focus on machine learning applications in bioinformatics and information retrieval. Dr. Zhang published more than 100 refereed papers in prestigious international conferences and journals including TPAMI, TIP, TNNLS, ICDM, CVPR, ICCV, ECCV, and ECML. She currently holds 5 US patents and 14 China patents. She is appointed as the Chief Expert for a 863 project by Ministry of science and technology of China. She was selected as a young star of science and technology in Shanghai, won several best paper awards of international journals and conferences, and directed one Outstanding Doctorate Dissertations awarded by Chinese Association for Artificial Intelligence.

Publications

Books:
  1. L. Cao, H. Motoda, J. Srivastava, E.-P. Lim, I. King, P. S.Yu, W. Nejdl, G. Xu, G. Li, Y. Zhang (Eds.). Behavior and Social Computing. Springer. International Workshop on Behavior and Social Informatics, BSI 2013, Gold Coast, Australia, April 14-17, and International Workshop on Behavior and Social Informatics and Computing, BSIC 2013, Beijing, China, August 3-9, 2013.
Refereed Journal Papers:
  1. C. Huang, Q. Xu, Y. Wang, Y. Wang, Y. Zhang, “Self-Supervised Masking for Unsupervised Anomaly Detection and Localization“, IEEE Transactions on Multimedia, accepted.
  2. X. Chen, Y. Zhang*, I. Tsang, Y. Pan, J. Su, “Towards Equivalent Transformation of User Preferences in Cross Domain Recommendation“, ACM Transactions on Information Systems (TOIS), accepted.
  3. M. Li, S. Chen*, Y. Shen, G. Liu, I. Tsang, Y. Zhang*, “Online Multi-Agent Forecasting with Interpretable Collaborative Graph Neural Networks“, IEEE Transactions on Neural Networks and Learning Systems, accepted.
  4. M. Li, S. Chen, Y. Shen, G. Liu, I. Tsang, Y. Zhang, “Online Multi-Agent Forecasting with Interpretable Collaborative Graph Neural Networks“, IEEE Transactions on Neural Networks and Learning Systems, accepted.
  5. J. Liu, Y. Zhao, S. Chen, Y. Zhang*, “A 3D Mesh-Based Lifting-and-Projection Network for Human Pose Transfer“, IEEE Transactions on Multimedia, accepted.
  6. M. Li, S. Chen*, X. Chen, Y. Zhang*, Y. Wang, Q. Tian, “Symbiotic Graph Neural Networks for 3D Skeleton-based Human Action Recognition and Motion Prediction“, IEEE Transactions on Pattern Analysis and Machine Intelligence, accepted.
  7. P. Zhao, L. Xie, Y. Zhang*, Q. Tian, “Actionness-guided Transformer for Anchor-free Temporal Action Localization“, IEEE Signal Processing Letters, 29:194-198, 2022.
  8. F. Ye, C. Huang, J. Cao, M. Li, Y. Zhang*, C. Lu, “Attribute Restoration Framework for Anomaly Detection“, IEEE Transactions on Multimedia, 24:116-127, 2022.
  9. X. Chen, S. Chen, J. Yao, H. Zheng, Y. Zhang*, I. Tsang, “Learning on Attribute-Missing Graphs“, IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(2):740-757, 2022.
  10. M. Li, S. Chen, Y. Zhao, Y. Zhang, Y. Wang, Q. Tian, “Multiscale Spatio-Temporal Graph Neural Networks for 3D Skeleton-Based Motion Prediction“, IEEE Transactions on Image Processing, 30:7760-7775, 2021.
  11. S. Feng, B. Liu, Y. Zhang*, X. Zhang, Y. Li, “Two-Stream Compare and Contrast Network for Vertebral Compression Fracture Diagnosis“, IEEE Transactions on Medical Imaging, 40(9):2496-2506, 2021.
  12. C. Ma, Q. Xu, X. Wang, B. Jin, X. Zhang, Y. Wang, Y. Zhang*, “Boundary-aware Supervoxel-level Iteratively Refined Interactive 3D Image Segmentation with Multi-agent Reinforcement Learning“, IEEE Transactions on Medical Imaging, 40(10):2563-2574, 2021.
  13. P. Zhao, L. Xie, Y. Zhang*, Q. Tian, “Universal-to-Specific Framework for Complex Action Recognition“, IEEE Transactions on Multimedia, 23:3441-3453, 2021.
  14. X. Chen, J. Yao, M. Li, Y. Zhang*, Y. Wang, “Decoupled Variational Embedding for Signed Directed Networks“, ACM Transactions on the Web, 15(1), Article 3 (October 2020), 31 pages.
  15. Y. Zhang, Y. Zhang*, “Learning Robust Shape-based Features for Domain Generalization“, IEEE Access, 8:63748-63756, 2020.
  16. Z. Tan, Y. Zhang*, W. Hu, “Online Prediction of Video Popularity in OVSs: A Video Age-Sensitive Model With Beyond Views Features“, IEEE Transactions on Broadcasting, 66(2):241-250, 2020.
  17. Y. Zhang, Y. Zhang*, W. Cai, “A Unified Framework for Generalizable Style Transfer: Style and Content Separation“, IEEE Transactions on Image Processing, 29(1):4085-4098, 2020.
  18. J. Yao, J. Wang, I. W. Tsang*, Y. Zhang*, J. Sun, C. Zhang, R. Zhang, “Deep Learning from Noisy Image Labels with Quality Embedding“, IEEE Transactions on Image Processing, 28(4):1909-1922, 2019.
  19. Z. Tan, Y. Zhang*, “Predicting the Top-N popular videos via a cross-domain hybrid model“, IEEE Transactions on Multimedia, 21(1):147-156, 2019.
  20. Z. Chen, Z. Xu, Y. Zhang*, X. Gu, “Query-free Clothing Retrieval via Implicit Relevance Feedback“, IEEE Transactions on Multimedia, 20(8):2126-2137, 2018.
  21. Z. Xu, S. Huang, Y. Zhang*, D. Tao*, “Webly-Supervised Fine-Grained Visual Categorization via Deep Domain Adaptation“, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 40(5): 1100-1113, 2018.
  22. J. Yao, Y. Wang*, Y. Zhang*, J. Sun, J. Zhou, “Joint Latent Dirichlet Allocation for Social Tags“, IEEE Transactions on Multimedia, 20(1):224-237, 2018.
  23. Y. Zhang, W. Cai, W. Wang, Y. Zhang*, “Stopping Criterion for Active Learning with Model Stability“, ACM Transactions on Intelligent Systems and Technology, 9(2), Article No. 19, 2017.
  24. W. Cai, Y. Zhang, Y. Zhang*, S. Zhou, W. Wang, Z. Chen, C. Ding, “Active Learning for Classification with Maximum Model Change“, ACM Transactions on Information Systems (TOIS), 36(2), 15, 2017.
  25. W. Cai, M. Zhang, Y. Zhang*, “Batch Mode Active Learning for Regression with Expected Model Change“, IEEE Transactions on Neural Networks and Learning Systems, 28(7):1668-1681, 2017.
  26. Z. Xu, D. Tao, S. Huang, Y. Zhang*, “Friend or Foe: Fine-Grained Categorization with Weak Supervision“, IEEE Transactions on Image Processing, 26(1):135-146, 2017.
  27. Z. Tan, Y. Wang*, Y. Zhang, J. Zhou, “A Novel Time Series Approach for predicting the long-term popularity of Online Videos“, IEEE Trans. on Broadcasting, 62(2):436-445, 2016.
  28. Z. Xu, Z. Hong, Y. Zhang*, J. Wu, A. C. Tsoi, D. Tao, “Multinomial Latent Logistic Regression for Image Understanding“, IEEE Transactions on Image Processing, 25(2):973-987, 2016.
  29. B. Long, J. Bian, O. Chapelle, Y. Zhang, Y. Inagakiy, Y. Chang, “Active Learning for Ranking through Expected Loss Optimization“, IEEE Transactions on Knowledge and Data Engineering, 27(5):1180-1191, 2015.
  30. Y. Zhang*, W. Chen, H. Zha, X. Gu, “A Time-Topic Coupled LDA Model for IPTV User Behaviors“, IEEE Trans. on Broadcasting, 61(1):56-65, 2015.
  31. W. Cai, M. Zhang, Y. Zhang, “Active learning for ranking with sample density“, Information Retrieval Journal, 18(2):123-144, 2015.
  32. W. Cai, M. Zhang, Y. Zhang*, “Active Learning for Web Search Ranking via Noise Injection“, ACM Transactions on the Web (TWEB), 9(1): article No. 3, 2015 (Source code).
  33. Y. Liu, Y. Qian, N. Chen, T. Fu, Y. Zhang, K. Yu, “Deep Feature for Text-dependent Speaker Verification”, Speech Communication, 73:1-13, 2015.
  34. Z. Xu, Y. Zhang*, L. Cao, “Social Image Analysis from a Non-IID Perspective“, IEEE Transactions on Multimedia, 16(7):1986-1998, 2014.
  35. Y. Zhang, X. Yang, H. Zha, “Behaviors of IPTV Users“, IEEE Trans. on Intelligent Systems, 29(4):76-78, 2014.
  36. M. Li, J. Li, Y. Ou, Y. Zhang, D. Luo, M. Bahtia, L. Cao, “Coupled K-Nearest Centroid Classification for Non-iid Data“, T. Computational Collective Intelligence 15: 89-100, 2014.
  37. Y. Wang, D. He, W. Zhang, Y. Guan, Y. Wang, Y. Zhang, H. Hui, “An Urban-Rural Dual Structure for the Digital Terrestrial Television Broadcasting System of FOBTV“, IEEE Trans. on Broadcasting, 60(2): 287-290, 2014.
  38. Y. Zhang, W. Chen, Z. Yin, “Collaborative filtering with social regularization for TV program recommendation“, Knowledge-Based Systems, Vol. 54, pp. 310-317, 2013. (data and source code)
  39. K. Shen, J. Wu, Y. Zhang, Y. Han, X. Yang, and L. Song, “Reorder User’s Tweets“, ACM TIST, vol.4(1), 2013.
  40. O. Chapelle, P. Shivaswamy, S. Vadrevu, K. Weinberger, Y. Zhang, and B. Tseng, “Boosted Multi-task Learning“, Machine Learning, vol. 85(1-2), 149-173, 2011. (g-scholar)
  41. H. Xiong, Y. Zhang, X. Chen, and J. Yu, “Cross-platform Microarray Data Integration using the Normalised Linear Transform“, The International Journal of Data Mining and Bioinformatics, vol. 4(2), 142-157, 2010. (g-scholar)
  42. H. Xiong, Y. Zhang, and X. Chen, “Data-dependent Kernel Machines for Microarray Data Classification“, IEEE/ACM Transaction on Computational Biology and Bioinformatics (TCBB), vol. 4(4), 583-595, 2007. (g-scholar)
  43. Y. Zhang, H. Zha, C. Chu, and X. Ji, “Towards Inferring Protein Interactions: Challenges and Solutions“, EURASIP Journal on Applied Signal Processing 2006 (2006), Article ID 37349, 14 pages. (g-scholar)
  44. Y. Zhang, C. H. Chu, Y. Chen, H. Zha, and X. Ji, “Splice Site Prediction Using Support Vector Machines with a Bayes Kernel“, Expert Systems with Applications, (special issue on Intelligent Bioinformatics Systems), 30(1):73-81, 2006. (g-scholar)
  45. J. Z. Wang, K. Grieb, Y. Zhang, C. Chen, Y. Chen, and J. Li, “Machine Annotation and Retrieval for Digital Imagery of Historical Materials“, International Journal on Digital Libraries, 6(1):18-29, Springer-Verlag, 2005. (g-scholar)
  46. Y. Zhang, J.-M. Chandonia, C. Ding and S. R. Holbrook, “Comparative Mapping of Sequence-based and Structure-based Protein Domains“, BMC Bioinformatics, 2005, 6:77. (g-scholar)
  47. Y. Zhang, X. Ji, C. H. Chu, and H. Zha, “Correlating Summarization of Multi-source News with K-Way Graph Bi-clustering“, ACM SIGKDD explorations (special issue on Web Content Mining), 6(2):34-42, 2004. (g-scholar)
Refereed Conference Papers:
  1. Z. Zhou, J. Yao, Y. Wang*, B. Han, Y. Zhang*, “Contrastive Learning with Boosted Memorization“, ICML 2022, accepted.
  2. F. Chang, C. Wu, Y. Wang, Y. Zhang, X. Chen, Q. Tian, “Boundary-Enhanced Self-Supervised Learning for Brain Structure Segmentation“, MICCAI 2022, accepted.
  3. W. Liu, C. Ma, Y. Yang, W. Xie, Y. Zhang, “Transforming the Interactive Segmentation for Medical Imaging“, MICCAI 2022, accepted.
  4. B. Guo, X. Zhang, H. Wu, Y. Wang*, Y. Wang, Y. Zhang, “LAR-SR: A Local Autoregressive Model for Image Super Resolution“, CVPR 2022, accepted.
  5. Y. Huang, X. Zhang, Y. Fu, S. Chen, Y. Zhang, Y. Wang*, D. He, “Task Decoupled Framework for Reference-based Super-Resolution“, CVPR 2022, accepted.
  6. C. Xu, M. Li, Z. Ni, Y. Zhang, S. Chen, “GroupNet: Multiscale Hypergraph Neural Networks for Trajectory Prediction with Relational Reasoning“, CVPR 2022, accepted.
  7. Z. Cheng, S. Chen*, Y. Zhang*, “Spatio-temporal Graph Complementary Scattering Networks“, ICASSP 2022.
  8. L. Zhang, S. Feng, Y. Wang, Y. Wang, Y. Zhang*, Xin Chen, Q. Tian, “Unsupervised Ensemble Distillation for Multi-organ Segmentation“, IEEE International Symposium on Biomedical Imaging (ISBI) 2022.
  9. R. Zhang, Q. Xu, C. Huang, Y. Zhang*, Y. Wang, “Semi-supervised Domain Generalization for Medical Image Analysis“, IEEE International Symposium on Biomedical Imaging (ISBI) 2022.
  10. Z. Cheng, S. Chen, Y. Zhang, “Spatio-temporal Graph Complementary Scattering Networks“, ICASSP 2022, accepted.
  11. L. Zhang, S. Feng, Y. Wang, Y. Wang, Y. Zhang, “Unsupervised Ensemble Distillation for Multi-organ Segmentation“, IEEE International Symposium on Biomedical Imaging (ISBI) 2022, accepted.
  12. R. Zhang, Q. Xu, C. Huang, Y. Zhang, Y. Wang, “Semi-supervised Domain Generalization for Medical Image Analysis“, IEEE International Symposium on Biomedical Imaging (ISBI) 2022, accepted.
  13. C. Huang, F. Ye, P. Zhao, Y. Zhang*, Y. Wang, Q. Tian, “ESAD: End-to-end Semi-supervised Anomaly Detection“, BMVC 2021.
  14. B. Tang, Y. Zhong, U. Neumann, G. Wang, Y. Zhang, S. Chen*, “Collaborative Uncertainty in Multi-Agent Trajectory Forecasting“, NeurIPS 2021.
  15. C. Ju, P. Zhao, S. Chen, Y. Zhang*, Y. Wang, Q. Tian, “Divide and Conquer for Single-frame Temporal Action Localization“, ICCV 2021, pp. 13455-13464.
  16. T. Cao, L. Du, X. Zhang, S. Chen, Y. Zhang, Y. Wang, “CaT: Weakly Supervised Object Detection with Category Transfer“, ICCV 2021, pp. 3070-3079.
  17. X. Zhang, S. Feng, Y. Zhou, Y. Zhang*, Y. Wang, “SAR: Scale-Aware Restoration Learning for 3D Tumor Segmentation“, MICCAI 2021, pp. 124-133.
  18. M. Hu, T. Song, Y. Gu, J. Chen, X. Luo, Y. CHen, S. Zhang, Y. Zhang, “Fully Test-time Adaptation for Image Segmentation“, MICCAI 2021, pp. 251-260.
  19. J. Chen, K. Yan, Y. Zhang, Y. Tang, X. Xu, Q. Liu, S. Sun, L. Huang, J. Xiao, A. Yuille, Y. Zhang, L. Lu, “Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining“, MICCAI 2021, pp. 765-774.
  20. F. Ye, H. Zheng, C. Huang, Y. Zhang*, “Deep Unsupervised Image Anomaly Detection: an Information Theoretic Framework“, ICIP 2021.
  21. Z. Cheng, S. Chen, Y. Zhang, “Semi-supervised 3D Hand-Object Pose Estimation via Pose Dictionary Learning“, ICIP 2021.
  22. L. Du, L. Hu, X. Zhang, Y. Zhang, Y. Zhang, Y. Wang, “Unsupervised Segmentation Framework with Active Contour Models for Cine Cardiac MRI“, ICIP 2021.
  23. Q. Xu, R. Zhang, Y. Zhang*, Y. Wang, Q. Tian, “A Fourier-based Framework for Domain Generalization“, CVPR 2021 (oral), pp. 14383-14392.
  24. H. Wu, J. Yao, Y. Zhang, Y. Wang, “Cooperative Learning for Noisy Supervision“, ICME 2021 (Oral).
  25. C. Xu, S. Chen*, M. Li, Y. Zhang*, “Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose Estimation“, AAAI 2021, pp. 3013-3021.
  26. C. Wen, Y. Pan, J. Chang, Y. Zhang, S. Chen, Y. Wang, M. Han, Q. Tian, “Handwritten Chinese Font Generation with Collaborative Stroke Refinement“, WACV 2021, pp. 3882-3891.
  27. K. Du, Y. Zhang*, H. Guan, “From Quantized DNNs to Quantizable DNNs“, BMVC 2020.
  28. M. Li, S. Chen*, Y. Zhang*, I. Tsang, “Graph Cross Networks with Vertex Infomax Pooling“, NeurIPS 2020 (Oral).
  29. K. Du, Y. Zhang*, H. Guan, Q. Tian, Y. Wang, S. Cheng, J. Lin, “FTL: A universal framework for training low-bit DNNs via Feature Transfer“, ECCV 2020.
  30. P. Zhao, L. Xie, C. Ju, Y. Zhang*, Y. Wang, Q. Tian, “Bottom-Up Temporal Action Localization with Mutual Regularization“, ECCV 2020. (Source code)
  31. Y. Xue, S. Feng, Y. Zhang*, X. Zhang, Y. Wang, “Dual-task Self-supervision for Cross-Modality Domain Adaptation“, MICCAI 2020, pp. 408-417.
  32. M. Hu, M. Mailard*, Y. Zhang*, T. Ciceri, G. L. Barbera, I. Bloch, P. Gori, “Knowledge distillation from multi-modal to mono-modal segmentation networks“, MICCAI 2020, pp. 773-781.
  33. M. Li, S. Chen*, Y. Zhao, Y. Zhang*, Y. Wang, Q. Tian, “Dynamic Multiscale Graph Neural Networks for 3D Skeleton-Based Human Motion Prediction“, CVPR 2020 (Oral), pp. 214-223. (Source code)
  34. Y. Hu, S. Chen*, Y. Zhang*, X. Gu, “Collaborative Motion Prediction via Neural Motion Message Passing“, CVPR 2020 (Oral), pp. 6319-6328. (Source code)
  35. X. Liao, W. Li, Q. Xu, X. Wang*, B. Jin*, X. Zhang, Y. Wang, Y. Zhang*, “Iteratively-Refined Interactive 3D Medical Image Segmentation with Multi-Agent Reinforcement Learning“, CVPR 2020, pp. 9394-9402
  36. Z. Tan, W. Hu, Y. Zhang, H. Ding, “Online Popularity Prediction of Video Segments Towards More Efficient Content Delivery Networks“, IEEE GLOBECOM 2019.
  37. H. Wu, J. Yao, J. Wang, Y. Chen, Y. Zhang*, Y. Wang, “Collaborative Label Correction via Entropy Thresholding“, ICDM 2019, pp. 1390-1395.
  38. Y. Zhou, Y. Zhang*, Y. Wang, Q. Tian, “Accelerate CNN via Recursive Bayesian Pruning“, ICCV 2019, pp. 3306-3315.
  39. M. Li, S. Chen, X. Chen, Y. Zhang, Y. Wang, Q. Tian, “Actional-Structural Graph Convolutional Networks for Skeleton-based Action Recognition“, CVPR 2019, pp. 3595-3603.
  40. Y. Hu, S. Chen, X. Chen, Y. Zhang* and X. Gu, “Neural Message Passing for Visual Relationship Detection“, ICML 2019 workshop on Learning and Reasoning with Graph-Structured Representations.
  41. H. Zheng, J. Yao, Y. Zhang*, I. Tsang, J. Wang, “Understanding VAEs in Fisher-Shannon Plane“, AAAI 2019, pp. 5917-5924.
  42. J. Yao, H. Wu, Y. Zhang, I. Tsang, J. Sun, “Safeguarded Dynamic Label Regression for Noisy Supervision“, AAAI 2019, pp. 9103-9110. (Source code)
  43. B. Han, J. Yao, G. Niu, M. Zhou, I. Tsang, Y. Zhang, M. Sugiyama, “Masking: A New Perspective of Noisy Supervision“, NeurIPS 2018: 5841-5851.
  44. K. Ren, Y. Fang, W. Zhang, S. Liu, J. Li, Y. Zhang, Y. Yu, J. Wang, “Learning Multi-touch Conversion Attribution with Dual-attention Mechanisms for Online Advertising“, CIKM 2018, pp. 1433-1442.
  45. H. Guan, G. Yao, Y. Zhang, Y. Gu, H. Zhao, Y. Zhang, “Deep Dual-view Network with Smooth Loss for Spinal Metastases Classification“, VCIP 2018.
  46. Y. Wang, L. Xie, S. Qiao, Y. Zhang*, W. Zhang, A. Yuille, “Multi-Scale Spatially-Asymmetric Recalibration for Image Classification“, ECCV 2018, pp. 523-539.
  47. J. Chang, Y. Gu, Y. Zhang*, Y. Wang, “Chinese Handwriting Imitation with Hierarchical Generative Adversarial Network“, BMVC 2018: 290.
  48. J. Wang, J. Yao, Y. Zhang*, R. Zhang, “Collaborative Learning for Weakly Supervised Object Detection“, IJCAI-ECAI-2018, pp. 971-977. (Source code)
  49. Y. Zhang, Y. Zhang*, W. Cai, “Separating Style and Content for Generalized Style Transfer“, CVPR 2018, pp. 8447-8455.
  50. Y. Li, M. Li, Y. Zhang, Y. Wang, “Unsupervised Local Facial Attributes transfer Using Dual Discriminative Adversarial Networks“, ICME 2018.
  51. Y. Zhou, S. Huang, Y. Zhang*, Y. Wang*, “Deep Hashing with Triplet Quantization Loss“, VCIP 2017.
  52. Z. Wang, Y. Gu, Y. Zhang*, J. Zhou, X. Gu, “Clothing Retrieval with Visual Attention Model“, VCIP 2017.
  53. Y. Wang, L. Xie*, C. Liu, S. Qiao, Y. Zhang*, W. Zhang, Q. Tian, A. Yuille, “SORT: Second-Order Response Transform for Visual Recognition“, ICCV 2017, pp. 1359-1368.
  54. S. Huang, Y. Xiong, Y. Zhang*, J. Wang, “Unsupervised Triplet Hashing for Fast Image Retrieval“, ACM Multimedia (Thematic Workshops) 2017, pp. 84-92.
  55. W. Wang, Y. Zhang, J. Hu, “Distance Metric Learning with Eigenvalue Fine Tuning“, IJCNN 2017, pp. 502-509.
  56. Y. Zhang, Y. Wang*, S. Zhou, W. Cai, Y. Zhang, “From Theory to Practice: Efficient Active Cost-sensitive Classification with Expected Error Reduction“, SDM 2017, pp. 153-161.
  57. H. Zheng, J. Yao, Y. Zhang, “Describing Geographical Characteristics with Social Images“, MMM 2017, pp. 115-126.
  58. J. Yao, Y. Zhang, I. Tsang, J. Sun, “Discovering User Interests from Social Images“, MMM 2017, pp. 160-172.
  59. Z. Rao, J. Yao, Y. Zhang, R. Zhang, “Preference Aware Recommendaction based on Categorical Information“, ICMLA 2016, pp. 865-870.
  60. Y. Xiong, N. Liu, Z. Xu, Y. Zhang, “A Parameter Partial-sharing CNN Architecture for Cross-Domain Clothing Retrieval“, VCIP 2016, pp. 1-4.
  61. J. Hou, Y. Zhang, X. Gu, “Synergy and Antagonism in Online Advertising“, BDCAT 2016, pp. 293 – 301.
  62. S. Huang, Z. Xu, D. Tao, Y. Zhang, “Part-Stacked CNN for Fine-Grained Visual Categorization“, CVPR 2016, pp. 1173 – 1182.
  63. X. Chen, J. Yao, Y. Zhang, “Online Learning Algorithm for Collective LDA“, ICMLA 2015, pp. 251 – 258.
  64. Z. Xu, S. Huang, Y. Zhang, D. Tao, “Augmenting Strong Supervision Using Web Data for Fine-grained Categorization“, ICCV 2015, pp. 2524 – 2532.
  65. J. Hu, Y. Wang and Y. Zhang, “IOHMM for Location Prediction with Missing Data“, DSAA 2015, pp. 1-10.
  66. J. Yao, Y. Zhang, Z. Xu, J. Sun, J. Zhou, X. Gu, “Joint Latent Dirichlet Allocation for Non-IID Social Tags“, ICME2015: 1-6.
  67. Y. Zhang, Y. Wei, J. Ren, “Multi-Touch Attribution in Online Advertising with Survival Theory“, ICDM2014, pp. 687-696.
  68. W. Wang, W. Cai, Y. Zhang, “Stability-based Stopping Criterion for Active Learning“, ICDM2014, pp. 1019-1024.
  69. W. Cai, Y. Zhang, S. Zhou, W. Wang, C. Ding, X. Gu, “Active Learning for Support Vector Machines with Maximum Model Change“, ECML/PKDD2014, pp. 211-226.
  70. Z. Xu, D. Tao, Y. Zhang, J. Wu, A. Tsoi, “Architectural Style Classification using Multinomial Latent Logistic Regression“, ECCV2014, pp. 600-615.
  71. M. Zhang, C. Ding, Y. Zhang, F. Nie, “Feature Selection at the Discrete Limit“, AAAI2014, pp. 1355-1361.
  72. Y. Zhao, X. Qi, Z. Liu, Y. Zhang, T. Zheng, “Mining Medical Records with a KLIPI Multi-Dimensional Hawkes Model“, KDD workshop on Healthcare Informatics.
  73. Z. Tan, Y. Zhang, C. Li, N. Liu, “Lifetime Popularity Prediction for Online Videos“, in Proc. of IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB2014), 2014.
  74. M. Li, J. Li, Y. Ou, Y. Zhang, D. Luo, M. Bahtia, L. Cao, “Learning Heterogeneous Coupling Relationships between Non-IID Terms“, in Agent and Data Mining Interaction, LNAI, pp 79-91, 2014.
  75. Y. Wei, K. Zhou, Y. Zhang, H. Zha, “Learning the Hotness of Information Diffusions with Multi-Dimensional Hawkes Processes“, in Agent and Data Mining Interaction, LNAI, pp. 92-110, 2014.
  76. J. Yan, Y. Tian, H. Zha, X. Yang, Y. Zhang, S. Chu, “Joint optimization for consistent multiple graph matching“, in Proc. of ICCV 2013, pp. 4321-4328.
  77. W. Cai, Y. Zhang, J. Zhou, “Maximizing Expected Model Change for Active Learning in Regression“, in Proc. of ICDM 2013, pp. 51-60 (Source code).
  78. J. Qiu, Y. Zhang, J. Sun, “Face Recognition in Open World Environment“, in Proc. of VCIP 2013.
  79. R. Li, Y. Zhang, “Social-Correlation Based Mutual Reinforcement for Short Text Classification and User Interest Tagging“, in Proc. of ADMA 2013.
  80. W. Chen, Y. Zhang, and H. Zha, “Mining IPTV User Behaviors with a Coupled LDA Model“, in Proc. of IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB2013), 2013.
  81. F. Ye, C. Zhang, Y. Zhang, and C. Ma, “Real-time TV Logo Detection based on Color and HOG Features“, in Proc. of IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB2013), 2013.
  82. Z. Xu, Y. Zhang, “Automatic Generated Recommendation for Movie Trailers“, in Proc. of IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB2013), 2013.
  83. W. Cai, Y. Zhang, “Variance Maximization via Noise Injection for Active Sampling in Learning to Rank“, in Proc. of the 21th ACM International Conference on Information and Knowledge Management (CIKM’12), pp.1809-1813, 2012.
  84. Y. Tian, J. Yan, H. Zhang, Y. Zhang, X. Yang and H. Zha. “On the Convergence of Graph Matching: Graduated Assignment Revisited“, in proceedings of the 12th European Conference on Computer Vision (ECCV’12), pp.821-835, 2012.
  85. W. Cai, Y. Zhang, “Incorporating Density in Active Learning with Application to Ranking“, in Proc. of ALRA: Active Learning in Real-world Applications (Workshop ECML-PKDD’12), 2012.
  86. Z. Yin, Y. Zhang, “Measuring Pair-wise Social Influence in Microblog“, in Proc. of 2012 ASE/IEEE International Conference on Social Computing and 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust, pp.502-507, 2012.
  87. Z. Yin, W. Chen, Y. Zhang, R. Zong, “Discovering Patterns of Advertisement Propagation in Sina-Microblog“, In Proceedings of the Sixth International Workshop on Data Mining for Online Advertising and Internet Economy (ADKDD’12), 2012.
  88. O. Chapelle, P. Shivaswamy, S. Vadrevu, K. Weinberger, Y. Zhang, B. Tseng, “Multi-Task Learning for Boosting with Application to Web Search Ranking“, in Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD2010), pp. 1189-1198. (g-scholar)
  89. B. Long, O. Chapelle, Y. Zhang, Y. Chang, Z. Zheng, B. Tseng, “Active Learning for Ranking through Expected Loss Optimization“, in Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval (SIGIR2010), 2010, pp.267-274.(g-scholar).
  90. Y. Yue, Y. Gao, O. Chapelle, Y. Zhang, T. Joachims, “Learning More Powerful Test Statistics for Click-Based Retrieval Evaluation“, in Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval (SIGIR2010), 2010, pp.507-514. .(g-scholar).
  91. O. Chapelle, D. Metzler, Y. Zhang, P. Grinspan, “Expected Reciprocal Rank for Graded Relevance“, in Proc. of the Ninth International Conference on Information and Knowledge Management (CIKM), 2009, 621-630. (g-scholar)
  92. B. Long, S. Lamkhede, S. Vadrevu, Y. Zhang, B. Tseng, “A Risk Minimization Framework for Domain Adaptation“, in Proc. of the Ninth International Conference on Information and Knowledge Management (CIKM), 2009, 1347-1356.(g-scholar)
  93. O. Chapelle and Y. Zhang, “A Dynamic Bayesian Network Click Model for Web Search Ranking“, in Proc. of the 18th International World Wide Web Conference (WWW), 2009, pp. 1-10. (g-scholar)
  94. K. Chen, Y. Zhang, Z. Zheng, H. Zha, and G. Sun, “Adapting ranking functions to user preference“, In Proc. of the DBRank workshop at IEEE conference on Data Engineering, 2008, pp.580-587. (g-scholar)
  95. A. Chen, Y. Zhang, and G. Sun, “A Two-Stage Approach to Chinese Part-of-Speech Tagging“, in Proc. of the Sixth SIGHAN Workshop on Chinese Language Processing (the Fourth International Chinese Language Processing Bakeoff ), January 2008. (g-scholar)
  96. H. Xiong, Y. Zhang, and X. Chen, “Normalized Linear Transform for Cross-Platform Microarray Data Integration“, in Proc. of the Sixth International Conference on Machine Learning and Applications (ICMLA), 2007, pp. 612-617. (g-scholar)
  97. C. Ding, Y. Zhang, T. Li, and S. Holbrook, “Biclustering Protein Complex Interactions with a Biclique Finding Algorithm“, in Proc. of the 6th IEEE International Conference on Data Mining (ICDM), 2006, pp. 178-187. (g-scholar)
  98. Y. Chen, Y. Zhang, and X. Ji, “Size Regularized Cut for Data Clustering“, Advances in Neural Information Processing Systems (NIPS) 18, MIT Press, Cambridge, MA, pp. 211-218, 2006. (g-scholar)
  99. Y. Zhang, Y. Chen, and X. Ji, “Motif Discovery as a Multiple-Instance Problem“, in Proc. of the 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2006, pp. 805-809. (g-scholar)
  100. A. Senf, X.-W. Chen, and Y. Zhang, “Comparison of One-Class SVM and Two-Class SVM for Fold Recognition“, In Proc. of The 13th International Conference on Neural Information Processing, 2006, pp. 140-149. (g-scholar)
  101. Y. Zhang, H. Zha, C. H. Chu, and X. Ji, “Protein Interaction Inference as a MAX-SAT Problem“, in Proc. of the IEEE CVPR 2005 Workshop on Computer Vision Methods for Bioinformatics., San Diego, CA, U.S.A., 2005. [Winner of the Best Paper Award] (g-scholar)
  102. A. Chen, Y. Zhou, Y. Zhang, and G. Sun. “Unigram Language Model for Chinese Word Segmentation“, Fourth SIGHAN Workshop on Chinese Language Processing (Second International Chinese Segmentation Bakeoff), 2005. (g-scholar)
  103. D. Zhou, Y. Song, Y. Zhang, H. Zha, “Towards Discovering Organizational Structure from Email Corpus“, in Proc. of the 4th IEEE International Conference on Machine Learning and Applications (ICMLA 2005), Los Angeles, CA, U.S.A. 2005. (g-scholar)
  104. Y. Zhang, H. Zha, and C. H. Chu, “A Time-Series Biclustering Algorithm for Revealing Co-regulated Genes“, in Proc. of IEEE International Conference on Information and Technology: Coding and Computing, (ITCC 2005), 2005, pp. 32-37. (g-scholar)
  105. Y. Zhang, C. H. Chu, H. Zha, Y. Chen, and X. Ji, “A Probabilistic Kernel for Splice Site Prediction“, in Proc. of the 8th Joint Conference on Information Sciences, Salt Lake City, UT, July 21-26, 2005, pp. 1278-1281. (g-scholar)
  106. H. Xiong, X. He, C. Ding, Y. Zhang, V. Kumar, S. R. Holbrook, “Identification of Functional Modules in Protein Complexes via Hyperclique Pattern Discovery“, in Proc. of the Pacific Symposium on Biocomputing, (PSB), 2005. (g-scholar)
  107. Y. Zhang and J. Z. Wang, “Progressive Display of Very High Resolution Images using Wavelets“, Journal of American Medical Informatics Association, Symposium Supplement, vol. 2002 suppl., pp. 944-948, November 2002. [Nominated for the Best Paper Award] (g-scholar)
Thesis and Other Publications:
  1. S. Vadrevu, Y. Zhang, B. Tseng, G. Sun and X. Li. “Identifying regional sensitive queries in web search“, The 17th International World Wide Web Conference (WWW), 2008, pp. 1185-1186. (Poster) (g-scholar)
  2. Y. Zhang, “Towards Inferring Biologically Informative Protein-protein Interactions”, Ph.D Dissertation, School of Information Sciences and Technology, The Pennsylvania State University, August 2005. (g-scholar)
  3. Y. Zhang, H. Zha, J. Z. Wang and C. Chu, “Gene Co-regulation vs. Co-expression“, the Eighth Annual International Conference on Research in Computational Molecular Biology (RECOMB), San Diego (March 27-31, 2004)., Currents in Computational Molecular Biology, A. Gramada & P. Bourne (eds.) ACM Press, March 2004., pp 232-233. (Poster) (g-scholar)
  4. Y. Zhang, H. Zha, J. Z. Wang and C. Chu, “Clustering of Time-course Gene Expression Data“, the Eighth Annual International Conference on Research in Computational Molecular Biology (RECOMB), San Diego (March 27-31, 2004)., Currents in Computational Molecular Biology, A. Gramada & P. Bourne (eds.) ACM Press, March 2004., pp.240-241. (Poster) (g-scholar)
  5. H. Wang and Y. Zhang, “Book review: Shaping Web Usability: Interaction Design in Context“, Information Processing and Management, 39(4), 665-666, 2003. (g-scholar)
PATENTS
  1. Method and appartus for using B measures to learn balanced relevance functions from expert and user judgments. K. Chen, Y. Zhang, Z. Zheng, H. Zha and G. Sun, US patent 7,685,078.
  2. Identifying Regional Sensitive Queries in Web Search. Y. Zhang, S. Vadrevu, B. Tseng, G. Sun, and X. Li, US patent 7,949,672.
  3. System and method for cross domain learning for data augmentation. B. Long, S. Lamkhede, S. Vadrevu, Y. Zhang, B. Tseng, US patent 8,332,334.
  4. Click Model for Search Rankings. O. Chapelle and Y. Zhang, US patent 8,671,093.
  5. Automated User Behavior Feedback System for Whole Page Search Success Optimization. D. Ciemiewicz, Y. Zhang, B. Tseng, and J.-M. Langlois, US patent 8,832,101.
  6. 蔡文彬;张娅,一种基于机器学习的排序系统,发明专利,专利号:ZL201310429873.X,授权日期:2016/9/7
  7. 蔡文彬;张娅,一种基于主动学习的回归分析系统及方法,发明专利,专利号:ZL201310430125.3,授权日期:2016/7/6
  8. 徐哲;张娅,面向图像分享网站图片的多重配对相似度确定方法,发明专利,专利号:ZL201310442438.0,授权日期:2016/8/17
  9. 邱洁琼;张娅;孙军,一个面向开放环境的人脸识别方法,发明专利,专利号:ZL201310501113.5,授权日期:2017/1/18
  10. 陈唯源,张娅,查宏远,基于家庭收视纪录的家庭分析及节目推荐方法,发明专利,专利号:ZL201310425811.1,授权日期:2017/8/1
  11. 张娅;魏逸;王宇晨,一种基于分布式计算的互联网信息投放渠道优化系统,发明专利,专利号:ZL201410289052.5,授权日期:2017/10/31
  12. 张娅;王延峰;熊意超;徐哲,基于部分参数共享的深度卷积神经网络跨域服装检索方法,发明专利,专利号:ZL201610590701.4,授权日期:2019/08/06
  13. 王延峰;谭智一;张娅,一种基于用户情绪的在线视频热度预测方法及系统,发明专利,专利号:ZL201710131940.8,授权日期:2019/08/06
  14. 王延峰;张娅;郑煌杰;姚江超,一种基于社交媒体图片的地域分析;推荐方法及系统,发明专利,专利号:ZL201610523047.5,授权日期:2019/11/15
  15. 张娅;姚江超;王嘉杰;王延峰,在标签含噪情况下基于质量嵌入的图像分类方法及系统,发明专利,专利号:ZL201710599924.1,授权日期:2019/11/19
  16. 王延峰;周越夫;黄杉杉;张娅,一种有监督深度哈希快速图片检索方法及系统,发明专利,专利号:ZL201710555687.9,授权日期:2019/12/27
  17. 张娅;王延峰;陈卓翔;徐哲,通过间接相关反馈在无查源下的衣服图像检索系统及方法,发明专利,专利号:ZL201610561407.0,授权日期:2020/1/7
  18. 王延峰,张娅,黄杉杉,熊意超,基于卷积神经网络的无监督哈希快速图片检索系统及方法,发明专利,专利号:ZL201710071669.3,授权日期:2020/1/21
  19. 张娅;王仲豪;顾宇俊;王延峰,基于视觉注意力模型的高精度服装图像检索方法及系统,发明专利,专利号:ZL201710567746.4,授权日期:2020/3/31
  20. 王延峰;张娅;姚江超;孙军,基于社交图片的用户兴趣挖掘和用户推荐方法及系统,发明专利,专利号:ZL201610523079.5,授权日期:2021/6/29
  21. 张娅;王延峰;侯杰;彭诗奇,基于霍克斯过程的节目质量评价方法,发明专利,专利号:ZL201710124570.5,授权日期:2020/06/12
  22. 张娅;常杰;顾宇俊;王延峰,基于对抗网络的汉字字体迁移系统,发明专利,专利号:ZL201710741335.2,授权日期:2020/11/10
  23. 张娅;常杰;王延峰,一种多媒体页面视觉显著性预测方法及系统,发明专利,专利号:ZL201810343404.9,授权日期:2020/08/25
  24. 张娅;崔克楠;陈旭;姚江超;王延峰,基于协同学习的用户兴趣建模方法和系统,发明专利,专利号:ZL201811287804.9,授权日期:2021/4/2
  25. 王延峰;赵培森;张娅,从全局到类别特征表达学习的动作识别方法和系统,发明专利,专利号:ZL201811612590.8,授权日期:2020/8/4
  26. 张娅;陈旭;崔克楠;姚江超;王延峰,基于物品关联关系的序列化推荐方法,发明专利,专利号:ZL201811116273.7,授权日期:2021/6/1
  27. 张娅;陈旭;姚江超;李茂森;王延峰,基于变分解耦合方式对符号有向网络的表达学习方法,发明专利,专利号:ZL201811184604.0,授权日期:2021/6/4
  28. 张娅;汶川;常杰;王延峰,基于协同笔画优化的个性化手写体迁移方法和系统,发明专利,专利号:ZL201910195271.X,授权日期:2021/5/25
  29. 张娅;李智康;王延峰,基于协同学习的弱监督语义分割方法及系统,发明专利,专利号:ZL201910619773.0,授权日期:2021/6/1
  30. 张娅;张烨珣;蔡文彬;王延峰,基于少量样本生成的任意风格和内容的迁移方法和系统,发明专利,专利号:ZL201710957685.2,授权日期:2021/12/17
  31. 张娅;王嘉杰;姚江超;王延峰,基于协同学习的弱监督检测模型训练方法及系统,发明专利,申请号:201810328284.5
  32. 王延峰;周越夫;张娅,基于变分推断的逐层神经网络剪枝方法和系统,申请号:201910195272.4
  33. 张娅;张烨珣;王延峰,基于对抗学习的无监督领域适应方法;系统及介质,申请号:201910276847.5
  34. 张娅;李茂森;陈旭;王延峰,人体骨架动作识别方法;系统及介质,申请号:201910411801.X
  35. 王延峰;彭诗奇;张娅;赵晖;顾一峰;李跃华;姚光宇,适用于脊柱转移肿瘤骨质的质量分类方法及系统,申请号:201910881871.1
  36. 王延峰;彭诗奇;张娅;赵晖;顾一峰;李跃华;姚光宇,基于自训练和切片传播的弱监督脊椎椎体分割方法和系统,申请号:201910989817.9
  37. 王延峰;赖柏霖;张小云;张娅;赵晖;顾一峰;李跃华;姚光宇,脊骨脱位辅助诊断方法及系统,申请号:201910912803.7
  38. 张小云;李圣杨;张娅;王延峰;王晓霞;钟玉敏;姚晓芬,CT扫描图像的儿童神经母细胞瘤分割方法、系统及装置,申请号:201911206067.X
  39. 张娅;廖选;李文浩;徐琪森;王祥丰;金博;张小云;王延峰,交互式图像分割方法、系统及终端,申请号:201911405917.9
  40. 张娅;李茂森;赵阳桁;王延峰,面向人体骨架的运动预测方法及系统,申请号:202010014577.3
  41. 张娅;赵培森;王延峰,约束时域关系的视频动作定位方法和系统,申请号:202010032794.5
  42. 张娅;鞠陈;王延峰,一种基于自适应采样策略的弱监督视频时序动作检测方法和系统,申请号:202010403823.4
  43. 张娅;杜昆原;王延峰,一种基于特征迁移的低比特神经网络训练框架,申请号:202010780010.7
  44. 张娅;杜昆原;王延峰,可在线切换比特位宽的量化神经网络,申请号:202010929604.X
  45. 张娅;雪盈盈;冯世祥;张小云;王延峰,基于目标领域自监督学习的无监督领域适应方法和系统,申请号:202011041122.7
  46. 张小云;郑州;王晓霞;钟玉敏;姚小芬;张娅;王延峰,基于目标分割领域自学习的半监督学习领域方法和系统,申请号:202011297406.2
  47. 张小云;胡伟峰;姚小芬;郑州;钟玉敏;王晓霞;张娅;王延峰,基于专注误分割区域的交互式图像分割方法和系统,申请号:202011297385.4
  48. 张娅;张小嫚;张小云;王延峰,自监督模型预训练方法、系统及介质,申请号:202011567684.5
  49. 张娅;冯世祥;刘贝贝;张小云;李跃华,锥体压缩性骨折辅助诊断方法和系统,申请号:202110229959.2
  50. 张娅;黄潮钦;叶飞,基于图像属性恢复的图像异常检测方法和系统,申请号:202110206510.4
  51. 张小云;曹天悦;陈思衡;张娅;王钰;王延峰,一种基于迁移学习的弱监督目标检测方法及系统,申请号:202110556712.1
  52. 张小云;黄一轩;乔宇;董超;张娅;王延峰,基于离散表示学习的图像超分辨率方法和系统、终端,申请号:202110755689.9
  53. 张娅;姜文波;赵贵华;张小云;董洋轶;张毅军;王延峰;蔺飞;袁旭稚,人脸图像超分辨率方法和系统,申请号:202110749972.0
  54. 姜文波;赵贵华;张小云;郭柏松;张娅;蔺飞;袁旭稚;王延峰,基于可学习字典的人脸五官超分辨率方法和系统、介质,申请号:202110804781.X
  55. 张小云;杜连宇;张娅;王延峰;陈思衡;王钰,基于主动轮廓模型的无监督医学图像分割方法和系统,申请号:202110826817.4
  56. 张娅;鞠陈;赵培森;陈思衡;张小云;王延峰,一种单帧监督视频时序动作检测与分类方法及系统,申请号:202111190861.7
  57. 张娅;姜文波;赵贵华;张小云;董洋轶;张毅军;王延峰;蔺飞;袁旭稚,一种人脸图像修复方法及系统,申请号:202111496917.1
  58. 张娅;张小嫚;黄潮钦;王延峰,基于图层分解的自监督肿瘤分割系统,申请号:202111303258.5
  59. 姜文波;赵贵华;张小云;郭柏松;张娅;蔺飞;辛威;王延峰,基于局部自回归模型和离散词典的超分辨率方法及系统,申请号:202111475883.8
  60. 王延峰;黄潮钦;徐勤伟;张娅,基于自监督掩膜的图像异常检测和异常定位方法及系统,申请号:202111397389.4
  61. 王延峰;赵培森;张小云;张娅,渐进式特权信息蒸馏的在线动作检测方法和系统,申请号:202111388139.4