千赢国/qy88千嬴国际官网-手机版

师资队伍
张长水

教授

信息处理研究所 所长

电话: 010-62794624 010-62796872 Fax: (010)62786911
地点:北京市海淀区千赢国系


教育背景


1986年7月毕业于北京大学数学系,获得理学学士学位

1992年7月毕业于千赢国系,获得博士学位


工作履历


1992.7. - 1994.12. 在千赢国系任讲师

1995.1. - 2000.8. 在千赢国系任副教授

2000.9. - 现在 在千赢国系任教授


学术兼职


国际学术杂志Pattern Recognition的编委(Associate Editor)

“计算机学报”编委


研究领域


模式识别,机器学习,人工智能,计算机视觉等

研究领域
以及和工业界的合作



研究概况


深度学习,小样本学习,因果学习等


学术成果


编著书籍

1. 阎平凡,张长水,人工神经网络与模拟进化计算,清华大学出版社,2000,11,北京

2.《智能信息处理和智能控制》,浙江科学技术出版社,1999,合著

3. David Zhang,Automated Biometrics: Technologies and Systems, Kluwer Acdemic Publisher, USA, June,2000。合著

发表文章

International Journal

1. Jiang Lu, Sheng jin, Jian Liang and Changshui Zhang. Robust Few-Shot Learning for User-Provided Data. IEEE Transactions on Neural Networks and Learning Systems. 2020 (accepted, to appear)

2. Runpeng Cui, Zhong Cao, Weishen Pan, Changshui Zhang, Jianqiang Wang. Deep Gesture Video Generation with Learning on Regions of Interest. IEEE Transactions on Multimedia.2019 (accepted, to appear)

3. Kailun Wu, Yiwen Guo, and Changshui Zhang. Compressing Deep Neural Networks with Sparse Matrix Factorization. IEEE Transactions on Neural Networks and Learning Systems. 2019 (accepted, to appear)

4. Ziang Yan, Yiwen Guo, Changshui Zhang. Adversarial Margin Maximization Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence.2019 (accepted, to appear) code

5. Rui Lu, Zhiyao Duan, Changshui Zhang. Audio–Visual Deep Clustering for Speech Separation. IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 27, no. 11, pp. 1697-1712, Nov. 2019.

6. Nan Jiang, Sheng Jin, Changshui Zhang. Hierarchical automatic curriculum learning: Converting a sparse reward navigation task into dense reward. Neurocomputing 360(2019): 265-278.

7. Wenzheng Hu, Junqi Jin, Tie-yan Liu, Changshui Zhang. Automatically Design Convolutional Neural Networks by Optimization with Submodularity and Supermodularity. IEEE Transactions on Neural Networks and Learning Systems. 2019 (accepted, to appear)

8. Daqing Chang, Shiliang Sun, Changshui Zhang. An Accelerated Linearly-Convergent Stochastic L-BFGS Algorithm. IEEE Transactions on Neural Networks and Learning Systems. vol. 30, no. 11, pp. 3338-3346, Nov. 2019.

9. Runpeng Cui, Hu Liu, Changshui Zhang. A Deep Neural Framework for Continuous Sign Language Recognition by Iterative Training. IEEE Transactions on Multimedia,Vol. 21, No. 7, pp. 1880-1891, 2019

10. Rui Lu, Zhiyao Duan and Changshui Zhang. Listen and Look: Audio–Visual Matching Assisted Speech Source Separation IEEE Signal Processing Letters Vol. 25, No. 9, pp. 1315-1319, Sept. 2018

11. Chengzhe Yan, Kailun Wu and Changshui Zhang. A New Anchor-Labeling Method For Oriented Text Detection Using Dense Detection Framework IEEE Signal Processing Letters Vol. 25, No. 9, pp. 1295-1299, Sept. 2018

12. Chongliang Luo, Jian Liang, Gen Li, Fei Wang, Changshui Zhang, Dipak K. Dey, Kun Chen. Leveraging Mixed and Incomplete Outcomes via Reduced-Rank Modeling Journal of Multivariate Analysis Volume 167, 2018, Pages 378-394.

13. Dejun Chu, Rui Lu, Jin Li, Xintong Yu, Changshui Zhang and Qing Tao. Optimizing Top-k Multiclass SVM via Semismooth Newton Algorithm IEEE Transactions on Neural Networks and Learning Systems. Vol. 29, No. 12, pp. 6264-6275, Dec. 2018.

14. Daqing Chang, Ming Lin and Changshui Zhang. On the Generalization Ability of Online Gradient Descent Algorithm Under the Quadratic Growth Condition IEEE Transactions on Neural Networks and Learning Systems.Vol. 29, No. 10, pp. 5008-5019, Oct. 2018.

15. Jian Liang, Kun Chen, Ming Lin, Changshui Zhang, Fei Wang. Robust Finite Mixture Regression For Heterogeneous Targets. Data Mining and Knowledge Discovery November 2018, Volume 32, Issue 6, pp 1509–1560.

16. Jiang Lu, Jin Li, Ziang Yan, Fenghua Mei and Changshui Zhang. Attribute-Based Synthetic Network (ABS-Net): Learning More From Pseudo Feature Representations Pattern Recognition 80 (2018): 129-142

17. Kun, Fu; Jin, Li; Junqi, Jin; Changshui, Zhang. Image-Text Surgery: Efficient Concept Learning in Image Captioning by Generating Pseudo Pairs IEEE Transactions on Neural Networks and Learning Systems Vol. 29, No. 12, pp. 5910-5921, Dec. 2018.

18. Chengzhe Yan, Jie Hu and Zhang Changshui. Deep Transformer: A Framework for 2D Text Image Rectification From Planar Transformations Neurocomputing 289 (2018): 32-43

19. Jiang Lu, Jie Hu, Guannan, Zhao, Fenghua Mei and Changshui Zhang. An in-field automatic wheat disease diagnosis system Computers and Electronics in Agriculture 142 (2017): 369-379.

20. Dejun Chu, Changshui Zhang, and Qing Tao. A faster cutting plane algorithm with accelerated line search for linear SVM Pattern Recognition. Volume 67, Pages 127-138, July 2017

21. Qing Zhuo, Yanpin Ren, Yongheng Jiang, Changshui Zhang. Hands-On Learning Through Racing: Signal processing and engineering education through the China National Collegiate Intelligent Model Car Competition. IEEE Signal Processing Magazine. 2017, 34(1),31 - 39

22. Wenzheng Hu, Qing Zhuo, Jianke Li, Changshui Zhang. Fast Branch Convolutional Neural Network for Traffic Sign Recognition. IEEE Intelligent Transportation Systems Magazine. Vol.9, No.3, pp.114-126, Fall 2017

23. Kun Fu, Junqi Jin, Runpeng Cui, Fei Sha, Changshui Zhang. Aligning where to see and what to tell: image captioning with region-based attention and scene-specific contexts. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). Vol.39, No.12, pp. 2321-2334, 1 Dec. 2017

24. Haisheng Xu, Jian Wang, Jian Yuan, Chunxiao Jiang and Changshui Zhang. Generalized RQ Minimization With Applications in Array Transmit Beamforming IEEE Antennas and Wireless Propagation Letters Vol. 16, pp. 177-180, 2017.

25. Hana Godrich, Arye Nehorai, Ali Tajer, Maria Sabrina Greco and Changshui Zhang. Special Article Series on Signal Processing Education via Hands-On and Design Projects [From the Guest Editors] IEEE Signal Processing Magazine Vol. 34, No. 1, pp. 13-15, Jan. 2017

26. Zhaohui Wu, Yongdi Zhou, Zhongzhi Shi, Changshui Zhang, Guanglin Li, Xiaoxiang Zheng, Nenggan Zheng, and Gang Pan. Cyborg Intelligence: Recent Progress and Future Directions IEEE Intelligent Systems Vol. 31, No. 6, pp. 44-50, Nov.-Dec. 2016.

27. Min Wu, Adi Hajj-Ahmad, Matthias Kirchner, Yanpin Ren, Changshui Zhang and Patrizio Campisi. Location Signatures That You Don't See: Highlights from the IEEE Signal Processing Cup 2016 Student Competition [SP Education] IEEE Signal Processing Magazine Vol. 33, No. 5, pp. 149-156, Sept. 2016

28. Hongwei Qin, Xiu Li, Jian Liang, Yigang Peng, and Changshui Zhang. DeepFish: Accurate underwater live fish recognition with a deep architecture Neurocomputing 187 (2016): 49-58.

29. Zhenwei Shi, Zhengxia Zou and Changshui Zhang. Real-Time Traffic Light Detection With Adaptive Background Suppression Filter IEEE Transactions on Intelligent Transportation Systems Vol. 17, No. 3, pp. 690-700, March 2016.

30. Ming Lin, Lijun Zhang, Rong Jin, Shifeng Weng, Changshui Zhang. Online Kernel Learning with Nearly Constant Support Vectors. Neurocomputing 179 (2016): 26-36.

31. Zhenwei Shi, Zhengxia Zou, Changshui Zhang. Real Time Traffic Light Detection with Adaptive Background Suppression Filter. IEEE Transactions on Neural Networks and Learning Systems.

32. Zhen Hu, Ming Lin, Changshui Zhang. Dependent Online Kernel Learning With Constant Number of Random Fourier Features. Neural Networks and Learning Systems, IEEE Transactions on. Volume 26, Issue 10, Pages 2464-2476, October 2015

33. Hou Guangdong, Runpeng Cui; Zheng Pan, Zhang Changshui. Tree-based Compact Hashing for Approximate Nearest Neighbor Search. Neurocomputing. Volume 166, Issue 20, Pages 271-281, October 2015

34. Shiming Xiang, Gaofeng Meng, Ying Wang, Chunhong Pan and Changshui Zhang. Image Deblurring with Coupled Dictionary Learning. International Journal of Computer Vision. Volume 114, Issue 2-3, Pages 248-271, September 2015

35. Zhenyu An, Zhenwei Shi, Ying Wu, Changshui Zhang. A Novel Unsupervised Approach to Discovering Regions of Interest in Traffic Images. Pattern Recognition. Volume 48, Issue 8, Pages 2581-2591, August 2015

36. Ming Lin, Fei Wang, Changshui Zhang. Large-Scale Eigenvector Approximation via Hilbert Space Embedding Nystrom. Pattern Recognition. Volume 48, Issue 5, Pages 1904-1912, May 2015

37. Zhigang Wang, Zengshun Zhao, Shifeng Weng, Changshui Zhang. Incremental Multiple Instance Outlier Detection. Neural Computing and Applications. Volume 26, Issue4, Pages 957-968, May 2015

38. Zheng Pan, Ming Lin, Guangdong Hou, Changshui Zhang. Damping Proximal Coordinate descent Algorithm for Non-convex Regularization. Neurocomputing. Volume 152, Issue 25, Pages 151-163, March 2015

39. Zhigang Wang, Zengshun Zhao, Shifeng Weng, Changshui Zhang. Solving one-class problem with outlier examples by SVM. Neurocomputing. Volume 149, Part A, Pages 100-105, February 2015

40. Wei Tang, Zhenwei Shi, Ying Wu and Changshui Zhang Sparse Unmixing of Hyperspectral Data Using Spectral a Priori Information. IEEE Transactions on Geoscience and Remote Sensing. Volume 53, Issue 2, February 2015, pp. 770-783

41. Pan, Zheng, and Changshui Zhang. Relaxed sparse eigenvalue conditions for sparse estimation via non-convex regularized regression. Pattern Recognition. Volume 48, Issue 1, Pages 231-243, January 2015

42. Zhen Guo, Bor Yann Liaw, Xinping Qiu, Lanlan Gao, Changshui Zhang. Optimal charging method for lithium ion batteries using a universal voltage protocol accommodating aging. Journal of Power Sources Volume 274, Issue 15, Pages 957-964, January 2015

43. Jin Junqi, Fu Kun, Zhang Changshui Traffic Sign Recognition With Hinge Loss Trained Convolutional Neural Networks. Intelligent Transportation Systems. 2014

44. Jingdong Wang, Huaizu Jiang, Yangqing Jia, Xian-Sheng Hua, Changshui Zhang and Long Quan. Regularized Tree Partitioning and Its Application to Unsupervised Image Segmentation. IEEE Transactions on Image Processing (TIP). Vol. 23, No. 4, April 2014

45. Han Li, Yashu Liu, Pinghua Gong, Changshui Zhang , Jieping Ye. Hierarchical Interactions Model for Predicting Mild Cognitive Impairment (MCI) to Alzheimer's disease. Plos One. Volume 9, Issue 1, e82450, January 2014

46. Ming Lin, Shifeng Weng, Changshui Zhang On the Sample Complexity of Random Fourier Features for Online Learning: How Many Random Fourier Features Do We Need? ACM Transactions on Knowledge Discovery from Data (TKDD).8.3(2014):13.

47. Chenping Hou, Feiping Nie, Changshui Zhang, Dongyun Yi, Yi Wu Multiple rank multi-linear SVM for matrix data classification. Pattern Recognition (PR). Volume 47, Issue 1, Pages 454-469, January 2014

48. Jiao Long, Zhenwei Shi, Wei Tang, and Changshui Zhang Single Remote Sensing Image Dehazing. IEEE Geoscience and Remote Sensing Letters (GRSL). VOL. 11, NO. 1, JANUARY 2014.

49. Zhen Guo, Xinping Qiu, Guangdong Hou, Bor Yann Liaw, Changshui Zhang. State of health estimation for lithium ion batteries based on charging curves . Journal of Power Sources, 2014.

50. Chenping Hou, Feiping Nie, Yuanyuan Jiao, Changshui Zhang, Yi Wu. Learning a subspace for clustering via pattern shrinking. Inf. Process. Manage. 49(4): 871-883 (2013)

51. Zhigang Wang, Zengshun Zhao, Changshui Zhang. Online Multiple Instance Regression . Chinese Physics BVolumn 22, No.9, 2013

52. Pinghua Gong, Jieping Ye, Changshui Zhang Multi-Stage Multi-Task Feature Learning. Journal of Machine Learning Research (JMLR) Volumn 14, Pages 2979-3010, 2013

53. Shizhun Yang, Chenping Hou, Changshui Zhang. Robust non-negative matrix factorization via joint sparse and graph regularization for transfer learning . Neural Computing and Applications, Volume 23, Number 2, Pages 541-559, August. 2013.

54. Zeng-Shun Zhao, Xiang Feng, Sheng-Hua Teng , Yi-Bin Li, Chang-Shui Zhang. Multi-scale Point Correspondence Using Feature Distribution and Frequency Domain Alignment. Mathematical Problems in Engineering, Volume 2012, doi:10.1155/2012/382369.

55. Nie, FP; Xiang, SM; Liu, Y; Hou, CP; Zhang, CS. Orthogonal vs. uncorrelated least squares discriminant analysis for feature extraction. Pattern Recognition Letters (PR). Volume 33, No. 5, pp. 485-491, 2012

56. Pinghua Gong, Changshui Zhang. Efficient Nonnegative Matrix Factorization via Projected Newton Method.Pattern Recognition (PR). Volume 45, Issue 9, pp. 3557-3565, September 2012

57. Shiming Xiang, Feiping Nie, Gaofeng Meng, Chunhong Pan, and Changshui Zhang. Discriminative Least Squares Regression for Multiclass Classification and Feature Selection. IEEE Transactions on Neural Netwrok and Learning System (T-NNLS). , 23(11), pp. 1738-1754, 2012.

58. Kun Gai, Zhenwei Shi, and Changshui Zhang. Blind Separation of Superimposed Moving Images Using Image Statistics. IEEE Transaction on pattern analysis and machine intelligence(TPAMI), Volumn 34, Issue 1, Pages 19-32. 2012.

59. Shizhun Yang, Ming Lin, Chenping Hou, Changshui Zhang, Yi Wu. A General Framework for Transfer Sparse Subspace Learning. Neural Computing and Applications. Volume 21, Number 7, Pages 1801-1817, August 2012.

60. Shiming Xiang, Gaofeng Meng, Ying Wang, Chunhong Pan, Changshui Zhang. Image Deblurring with Matrix Regression and Gradient Evolution. Pattern Recognition, Volumn 45, Issue 6, Pages 2164-2179, June 2011.

61. Shouchun Chen, Fei Wang, Yangqiu Song, Changshui Zhang. Semi-supervised Ranking Aggregation. Information Processing and Management, Volumn 47, Issue 3, Pages 415-25, May 2011.

62. Shiming Xiang, Feiping Nie, Chunhong Pan, Changshui Zhang. Regression Reformulations of LLE and LTSA with Locally Linear Transformation. IEEE Transactions on Systems, Man, and Cybernetics, Part B ( T-SMC-B), Volumn 41, Issue 5, Pages 1250-62. October 2011.

63. Shiming Xiang, Chunhong pan, Feiping Nie, and Changshui Zhang. Interactive Image Segmentation with Multiple Linear Reconstructions in Windows. IEEE Transactions on Multimedia, Volumn 13, Issue 2, Pages 342-352 , April 2011.

64. Chenping Hou, Feiping Nie, Fei Wang, Changshui Zhang, Yi Wu. Semi-Supervised Learning Using Negative Labels. IEEE Transactions on Neural Networks, Volumn 22, Issue 3, Pages 420-432, March 2011.

65. Zheng Wang, ShuichengYan, ChangshuiZhang. Active learning with adaptive regularization. Pattern Recognition, Volumn 44, Pages 2375-2383. 2011.

66. Pinghua Gong , Kun Gai and Changshui Zhang. Efficient Euclidean Projections via Piecewise Root Finding and Its Application in Gradient Projection. Neurocomputing, Volumn 74, Pages 2754-2766. 2011.

67. Fei Wang, Bin Zhao, Changshui Zhang. Unsupervised Large Margin Discriminative Projection. IEEE Transaction on Neural Networks(TNN), Volumn 22, Issue 9, Pages 1446-1456. 2011.

68. Feiping Nie, Zinan Zeng, Tsang Ivor, Dong Xu, Changshui Zhang. Spectral Embedded Clustering: A Framework for In-Sample and Out-of-Sample Spectral Clustering. IEEE Transactions on Neural Networks(TNN), Volumn 22, Issue 11, Pages 1796-1808. 2011.

69. Zhang Changshui, Hou Guangdong, Wang Jun. A Fast Algorithm Based On The Submodular Property For Optimization Of Wind Turbine Positioning. Renewable Energy 36 (2011), Pages 2951-2958. 2011.

70. Jianwen Zhang, Changshui Zhang. Multitask Bregman clustering. Neurocomputing, Volume 74, Issue 10, Pages 1720-1734. May 2011.

71. Zhiyao Duan, Bryan Pardo, Changshui Zhang. Multiple Fundamental Frequency Estimation by Modeling Spectral Peaks and Non-Peak Regions. IEEE Transactions on Audio, Speech and Language Processing, Volume 18, Issue 8, Pages 2121-2154. November 2010.

72. Feiping Nie, Shiming Xiang, Yun Liu, Changshui Zhang. A general graph-based semi-supervised learning with novel class discovery. NEURAL COMPUTING & APPLICATIONS, Volume 19, Issue 4, Pages 549-555. June 2010.

73. Fei Wang, Bin Zhao, Changshui Zhang. Linear Time Maximum Margin Clustering. IEEE Transations on Neural Networks, Volume 21, Issue 2, Pages 319-332. February 2010.

74. Feiping Nie, Dong Xu, Tsang Ivor Wai-Hung, Changshui Zhang. Flexible manifold embedding: a framework for semi-supervised and unsupervised dimension reduction.IEEE Transactions Image Process(ITIP), Volume 19, Issue 7, Pages 1921-1953. July 2010.

75. Chenping Hou, Changshui Zhang, Yi Wu, Feiping Nie. Multiple view semi-supervised dimensionality reduction.Pattern Recognition(PR), Volume 43, Issue 3, Pages 720-750. March 2010.

76. Changshui Zhang, Qutang Cai, Yangqiu Song. Boosting with pairwise constraints. NEUROCOMPUTING, Volume 73, Issue 4-6, Special Issue: Sp. Iss. SI, Pages 908-919. January 2010.

77. Changshui Zhang, Fei Wang. A multilevel approach for learning from labeled and unlabeled data on graphs.Pattern Recognition(PR), Volume 43, Issue 6, Pages 2301-2315. June 2010.

78. Changshui Zhang, Feiping Nie, Shiming Xiang. A General Kernelization Framework for Learning Algorithms Based on Kernel PCA. NEUROCOMPUTING, Volume 73, Issue: 4-6, Special Issue: Sp. Iss. SI, Pages 959-967, January 2010.

79. Shiming Xiang, Feiping Nie, and Changshui Zhang. Semi-Supervised Classification via Local Spline Regression.IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Volume 32, Issue 11, Pages 2039-2053. November 2010.

80. Shiming Xiang, Chunhong Pan, Feiping Nie, Changshui Zhang. TurboPixel Segmentation Using Eigen-Images.IEEE Transactions on Image Processing(ITIP), Volume 19, Issue 11, Pages 3024-3058. November 2010.

81. Shijun Wang, and Changshui Zhang. Collaborative Learning by Boosting in Distributed Environments.International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), Volume 24, Issue 5, Pages 763-789, 2010.

82. Fei Wang, Changshui Zhang, Tao Li. Clustering with Local and Global Regularization. IEEE Transactions on Knowledge and Data Engineering, Volume: 21 Issue: 12 Pages: 1665-78.December 2009.

83. Fei Wang, Xin Wang, Daoqiang Zhang, Changshui Zhang, Tao Li. marginFace: a novel face recognition method by average neighborhood margin maximization. Pattern Recognition(PR), Volume 42, Issue 11, Pages 2863-75. November 2009.

84. Feiping Nie, Shiming Xiang, Yangqing Jia, Changshui Zhang. Semi-supervised orthogonal discriminant analysis via label propagation. Pattern Recognition(PR), Volume 42, Issue 11, Pages 2615-2627.November 2009.

85. Dan Zhang, Fei Wang, Zhenwei Shi, Changshui Zhang. Interactive Localized Content-Based Image Retrieval with Multiple Instance Active Learning. Pattern Recognition(PR), Volume 43, Issue 2,Pages 478-484. February 2010, .

86. Changshui Zhang, Feiping Nie, Shiming Xiang, Chenping Hou. Soft Constraint Harmonic Energy Minimization for Transductive Learning and Its Two Interpretations. Neural Processing Letters (NPL), Volume 30, Issue 2, Pages 89-102. October, 2009.

87. Shiming Xiang,Feiping Nie,Yangqiu Song,Changshui Zhang,Chunxia Zhang. Embedding New Data Points for Manifold Learning via Coordinate Propagation. Knowledge and Information Systems(KAIS),Volume 19,Issue 2,Pages 159-184,2009.

88. Chenping Hou, Changshui Zhang, Yi Wu, Yuanyuan Jiao. Stable local dimensionality reduction approaches.Pattern Recognition(PR), Volume 42, Issue 9, Pages 2054-2120. September 2009.

89. Shiming Xiang,Feiping Nie,Changshui Zhang,Chunxia Zhang.Nonlinear Dimensionality Reduction with Local Spline Embedding. IEEE Transactions on Knowledge and Data Engineering(TKDE),Volume 21,Issue 9,Pages 1285-1298,September 2009.

90. Jingdong Wang, Fei Wang, Changshui Zhang, Helen C. Shen, Long Quan. Linear Neighborhood Propagation and Its Applications. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Volume 31,Number 9,Page 1600-1615,September 2009.

91. Shiming Xiang,Feiping Nie,Chunxia Zhang,Changshui Zhang.Interactive Natural Image Segmentation via Spline Regression. IEEE Transactions on Image Processing(TIP), Volume 18,Issue 7,Page 1623-1632,July 2009.

92. Chenping Hou, Changshui Zhang, Yi Wu. Learning an orthogonal and smooth subspace for image classification.IEEE Signal Processing Letters, Volume 16, Issue 4, Pages 303-309. April 2009.

93. Bin Zhao,Fei Wang,Changshui Zhang. Block Quantized Support Vector Ordinal Regression. IEEE Transactions on Neural Networks(TNN), Volume 20, Issue 5,Page 882-890,May 2009.

94. Gang Chen, Fei Wang, Changshui Zhang. Collaborative filtering using orthogonal nonnegative matrix tri-factorization. Information Processing and Management, Volume 45, Page 368-379.2009.

95. Feiping Nie,Shiming Xiang,Yangqiu Song,Changshui Zhang. Orthogonal locality minimizing globality maximizing projections for feature extraction. Optical Engineering, Volume 48,Number 1,January 2009.

96. Yangqiu Song, Changshui Zhang, Jianguo Lee, Fei Wang, Shiming Xiang, Dan Zhang. Semi-Supervised Discriminative Classification with Application to Tumorous Tissues Segmentation of MR Brain Images. Pattern Analysis and Applications (PAA),Volume 12,Page 99-115,2009.

97. Qutang Cai, Changshui Zhang, Chunyi Peng. Analysis of classification margin for classification accuracy with applications. Neurocomputing,Volume 72,Page 1960-1968, 2009.

98. Yangqing Jia,Feiping Nie,Changshui Zhang.Trace Ratio Problem Revisited. IEEE Transactions on Neural Network(NN),Volume 20,Number 4,Page 729-735,April 2009.

99. Zhenwei Shi,Changshui Zhang.Fast nonlinear autocorrelation algorithm for source separation.Pattern Recognition(PR),Volume 42,Number 9,Page 1732-1741,September 2009.

100. Feiping Nie,Shiming Xiang,Yangqiu Song,Changshui Zhang.Extracting the Optimal Dimensionality for Local Tensor Discriminant Analysis. Pattern Recognition(PR),Volume 42,Page 105-114,January 2009.

101. Yangqing Jia,Changshui Zhang. Front-view vehicle detection by Markov chain Monte Carlo method.Pattern Recognition(PR),Volume 42,Number 3,Page 313-321,March 2009.

102. Fei Wang, Changshui Zhang. Semi-supervised Learning Based on Generalized Point Charge Models. IEEE Transactions on Neural Networks (TNN), Volume 19, Number 7, Pages 1307-1311, July 2008.

103. Yangqiu Song, Feiping Nie, Changshui Zhang, Shiming Xiang. A Unified Framework for Semi-Supervised Dimensionality Reduction. Pattern Recognition(PR), Volume 41, Number 9, Pages 2789-2799, September 2008.

104. Yangqiu Song, Feiping Nie, Changshui Zhang. Semi-supervised Sub-manifold Discriminant Analysis. Pattern Recognition Letters, Volume 29, Number 13, Pages 1806-1813, October 2008.

105. Shiming Xiang, Feiping Nie, and Changshui Zhang. Learning a Mahalanobis distance metric for data clustering and classification. Pattern Recognition, Volume 41, Number 12, Pages 3600 - 3612, 2008.

106. Shiming Xiang, Feiping Nie, Yangqiu Song, and Changshui Zhang. Contour graph based human tracking and action sequence recognition. Pattern Recognition, Volume 41, Number 12, Pages 3653 - 3664, 2008.

107. Zhiyao Duan, Yungang Zhang, Changshui Zhang, and Zhenwei Shi. Unsupervised Single-Channel Music Source Separation by Average Harmonic Structure Modeling. IEEE Transaction on Audio, Speech, and Language Processing, Volume 16, Number 4, Pages 766-778, May 2008.

108. Shijun Wang, Mate S. Szalay, Changshui Zhang, and Peter Csermely. Learning and Innovative Elements of Strategy Adoption Rules Expand Cooperative Network Topologies. PLoS ONE 3(4): e1917. doi:10.1371/journal.pone.0001917, 2008.

109. Yangqiu Song and Changshui Zhang. Content Based Information Fusion for Semi-Supervised Music Genre Classification. IEEE Transaction on Multimedia, Volume 10, Number 1, Pages145-152, January, 2008.

110. Zhenwei Shi, Dan Zhang, and Changshui Zhang. MACBSE: Extracting signals with linear autocorrelations.Neurocomputing, Volume 71, Number 4-6, Pages 1082-1091, January 2008.

111. Fei Wang, Changshui Zhang. Label Propagation Through Linear Neighborhoods. IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume 20, Number 1, Pages 55-67, January 2008.

112. Zhenwei Shi, Changshui Zhang. Nonlinear innovation to blind source separation. Neurocomputing, Volume 71, Number 1-3, Pages 406-410, December 2007.

113. Zhenwei Shi, Changshui Zhang. Blind Source Extraction Using Generalized Autocorrelations. IEEE Transactions on Neural Networks, Volume 18, Number 5, Pages 1516-1524, September 2007.

114. Shiliang Sun, Changshui Zhang. The Selective Random Subspace Predictor for Traffic Flow Forecasting. IEEE Transactions on Intelligent Transportation Systems, Volume 8, Number 2, Pages 367-373, June 2007.

115. Fei Wang, Changshui Zhang. Robust Self-Tuning Semi-Supervised Learning. Neurocomputing, Volume 70, Number 16-18, Pages 2931-2939, October 2007.

116. Fei Wang, Jingdong Wang, Changshui Zhang, James T. Kwok. Face Recognition Using Spectral Features. Pattern Recognition, Volume 40,Number 10, Pages 2786-2797, October 2007.

117. Fei Wu, Jingrui He , Changshui Zhang. An Evolutionary System for Near-Regular Texture Synthesis. Pattern Recognition, Volume 40,Number 8, Pages 2271-2282, August 2007.

118. Zhenwei Shi, Changshui Zhang. Semi-blind Source Extraction for Fetal Electrocardiogram Extraction by Combining Non-Gaussianity and Time-Correlation. Neurocomputing, Volume 70, Number 7-9, Pages 1574-1581, March 2007.

119. Shiliang Sun, Changshui Zhang, Yue Lu. The Random Electrode Selection Ensemble for EEG Signal Classification. Pattern Recognition, Volume 41,Number 5, Pages 1663-1675, May 2008.

120. Shiliang Sun, Changshui Zhang, Dan Zhang. An Experimental Evaluation of Ensemble Methods for EEG Signal Classification. Pattern Recognition Letters, Volume 28,Number 15, Pages 2157-2163, November 2007.

121. Shiliang Sun, Changshui Zhang. Subspace Ensembles for Classification. Physica A: Statistical Mechanics and its Applications, Volume 385,Number 1, Pages 199-207, November 2007.

122. Jianguo Lee and Changshui Zhang. Classification of Gene-Expression Data: The Manifold based Metric Learning Way. Pattern Recognition, Volume 39,Number 12, Pages 2450-2463, December 2006.

123. Zhonglin Lin, Changshui Zhang, Wei Wu and Xiaorong Gao. Frequency recognition based on canonical correlation analysis for SSVEP-based BCIs. IEEE Transactions on Biomedical Engineering, Volume 53,Number 12, Pages 2610-2614, December, 2006.

124. Shiliang Sun, Changshui Zhang. Adaptive feature extraction for EEG signal classification. Medical and Biological Engineering and Computing, Volume 44,Number 10, Pages 931-935, October 2006.

125. Zhenwei Shi, Changshui Zhang. Energy Predictability to Blind Source Separation. Electronics Letters, Volume 42,Number 17, Pages 1006-1008, August 2006.

126. Jingrui He, Mingjing Li, Hong-Jiang Zhang, Hanghang Tong and Changshui zhang. Generalized Manifold-Ranking Based Image Retrieval. IEEE Transaction on Image Processing, Volume 15,Number 10, Pages 3170-3177, October 2006.

127. Shijun Wang, Zhongbao Kou and Changshui Zhang. Network Boosting on Different Networks. Physica A: Statistical Mechanics and its Applications, Volume 366,Number 1, Pages 561-570, July 2006.

128. Shiliang Sun, Changshui Zhang. An optimal kernel feature extractor and its application to EEG signal classification. Neurocomputing, Volume 69, Number 13-15, Pages 1743-1748, August 2006.

129. Zhenwei Shi and Changshui Zhang. Gaussian Moments for Noisy Complexity Pursuit. Neurocomputing, Volume 69, Number 7-9, Pages 917-921, March 2006.

130. Shiliang Sun, Changshui Zhang and Guoqiang Yu. A Bayesian Network Approach to Traffic Flow Forecasting.IEEE Transactions on Intelligent Transportation Systems, Volume 7, Number 1, Pages 124 - 132, March 2006.

131. Shijun Wang and Changshui Zhang. Price Formation Based on Particle-Cluster Aggregation. International Journal of Modern Physics C (IJMPC), Volume 16, Number 11, Pages 1811-1816, November 2005.

132. Shijun Wang and Changshui Zhang. Microscopic Model of Financial Markets Based on Belief Propagation.Physica A: Statistical Mechanics and its Applications, Volume 354, Pages 496-504, August 2005.

133. Xin Yao, Changshui Zhang, Jinwen Chen and Yanda Li. On the Formation of Degree and Cluster-Degree Correlations in Scale-Free Networks. Physica A: Statistical Mechanics and its Applications, Volume 353, Pages 661-673, August 2005.

134. Shifeng Weng, Changshui Zhang and Zhonglin Lin. Exploring the Structure of Supervised Data by Discriminant Isometric Mapping. Pattern Recognition, Volume 38, Number 4, Pages 599-601, April 2005.

135. Shifeng Weng, Changshui Zhang, Zhonglin Lin and Xuegong Zhang. Mining the Structural Knowledge of High Dimensional Medical Data Using Isomap. Medical and Biological Engineering and Computing, Volume 43, Number 3, Pages 410-412, June 2005.

136. Jianguo Lee, Jingdong Wang, Changshui Zhang and Zhaoqi Bian. Visual Object Recognition Using Probabilistic Kernel Subspace Similarity. Pattern Recognition, Volume 38, Number 7, Pages 997-1008, July 2005.

137. Baibo Zhang, Changshui Zhang and Xing Yi. Active Curve Axis Gaussian Mixture Models. Pattern Recognition, Volume 38, Number 12, Pages 2351-2362, December 2005.

138. Hanghang Tong, Jingrui He, Mingjing Li, Wei-Ying Ma, Hong-Jiang Zhang and Changshui Zhang. Manifold-Ranking Based Keyword Propagation for Image Retrieval. Journal on Applied Signal Processing, Volume 2006, Pages 79412.1-79412.10, 2006.

139. Shijun Wang and Changshui Zhang. Weighted Competition Scale-Free Network. Physical Review E, Volume 70, Number 6, Pages 066127.1-066127.6, December 2004.

140. Yungang Zhang, Chang Shui Zhang and David Zhang. Distance Metric Learning by Knowledge Embedding.Pattern Recognition, Volume 37, Number 1, Pages 161-163, January 2004.

141. Changshui Zhang, Jun Wang, Nanyuan Zhao and David Zhang. Reconstruction and analysis of multi-pose face images based on nonlinear dimensionality reduction. Pattern Recognition, Volume 37, Number 2, Pages 325-336, February 2004.

142. Baibo Zhang, Changshui Zhang and Xing Yi. Competitive EM Algorithm for Finite Mixture Models. Pattern Recognition, Volume 37, Number 1, Pages 131-144, February 2004.

143. Zhongbao Kou and Changshui Zhang. Reply Networks on a Bulletin Board System. Physical Review E, Volume 67, Number 3, Pages 036117.1-036117.6, March 2003.



International Conference

2020

144. Nan Jiang, Sheng Jin, Zhiyao Duan, Changshui Zhang. RL-Duet: Online Music Accompaniment for Real-time Human-Machine Interactive Duet Improvisation. The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20).New York City, NY, USA, 2020.

145. Jinlin Liu,Yuan Yao ,Wendi Hou ,Miaomiao Cui,Xuansong Xie,Changshui Zhang,Xian-Sheng Hua ,Boosting Semantic Human Matting with Coarse Annotations,CVPR 2020,Seattle, USA, June, 16-18, 2020

146. Shan You ,Tao Huang ,Mingmin Yang,Fei Wang,Chen Qian,Changshui Zhang ,GreedyNAS: Towards Fast One-Shot NAS with Greedy Supernet, CVPR 2020,Seattle, USA, June, 16-18, 2020

147. Tianhong Li,Jianguo Li,Zhuang Liu ,Changshui Zhang,Few Sample Knowledge Distillation for Efficient Network Compression, CVPR 2020,Seattle, USA, June, 16-18, 2020

2019

148. Ziang Yan*, Yiwen Guo*, Changshui Zhang. Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks. The 33rd Conference on Neural Information Processing Systems (NeurIPS) Vancouver, Canada, December 8-14, 2019 code

149. Xintong Yu*, Hongming Zhang*, Yangqiu Song, Yan Song, and Changshui Zhang. What You See is What You Get: Visual Pronoun Coreference Resolution in Conversations. Conference on Empirical Methods in Natural Language Processing (EMNLP). Hong Kong, China, 2019. code

150. Xintong Yu, Tszhang Guo, Kun Fu, Lei Li, Changshui Zhang and Jianwei Zhang. Image Captioning with Partially Rewarded Imitation Learning. International Joint Conference on Neural Networks (IJCNN) Budapest, Hungary, 2019

2018

151. Kailun Wu, Changshui Zhang. Deep Generative Adversarial Networks for the Sparse Signal Denoising 24th International Conference on Pattern Recognition (ICPR).IEEE, 2018: 1127-1132.

152. Lu, Rui, Zhiyao Duan, and Changshui Zhang. Multi-Scale Recurrent Neural Network for Sound Event Detection. 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

153. Jiang Lu, Zhong Cao, Kailun Wu, Gang Zhang and Changshui Zhang. Boosting Few-shot Image Recognition via Domain Alignment Prototypical Networks. The 2018 IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2018)

154. Yiwen Guo*, Chao Zhang*, Changshui Zhang, Yurong Chen.Sparse DNNs with Improved Adversarial RobustnessThe 32nd Conference on Neural Information Processing Systems (NeurIPS) Montreal, Canada, December 2-8, 2018.

155. Ziang Yan*, Yiwen Guo*, Changshui Zhang.Deep Defense: Training DNNs with Improved Adversarial Robustness The 32nd Conference on Neural Information Processing Systems (NeurIPS) Montreal, Canada, December 2-8, 2018. code

156. Hu Liu, Sheng Jin, Changshui Zhang.Connectionist Temporal Classification with Maximum Entropy Regularization The 32nd Conference on Neural Information Processing Systems (NeurIPS) Montreal, Canada, December 2-8, 2018. Code

2017

157. Jie Hu, Tszhang Guo, Ji Cao and Changshui Zhang. End-to-end Chinese Text Recognition. 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP) Montreal, QC, 2017, pp. 1407-1411.

158. Chengzhe Yan, Jie Hu, Runpeng Cui and Changshui Zhang. Robust Text Image Alignment with Template for Information Retrieval. 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC) Banff, AB, 2017, pp. 1874-1879.

159. Ziang Yan, Chengzhe Yan and Changshui Zhang. Rare Chinese Character Recognition by Radical Extraction Network. 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC) Banff, AB, 2017, pp. 924-929.

160. Rui Lu, Zhiyao Duan and Changshui Zhang. Metric learning based data augmentation for environmental sound classification 2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) New Paltz, NY, 2017, pp. 1-5.

161. Zhuang Liu, Jianguo Li, Zhiqiang Shen, Gao Huang, Shoumeng Yan, Changshui Zhang. Learning Efficient Convolutional Networks through Network Slimming International Conference on Computer Vision(ICCV) 2017

162. Rui Lu, Kailun Wu, Zhiyao Duan, Changshui Zhang. Deep ranking: triplet matchnet for music metric learningProceedings of the Acoustics, Speech and Signal Processing (ICASSP) New Orleans, America. March, 2017

163. Runpeng Cui, Hu Liu, Changshui Zhang. Recurrent Convolutional Neural Networks for Continuous Sign Language Recognition by Staged Optimization IEEE Computer Society Conference on Computer Vision and Pattern Recognition(CVPR) Honolulu, Hawaii, USA. July, 2017


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