师资队伍

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月毕业于清华大学自动化系，获得博士学位

1992.7. - 1994.12. 在清华大学自动化系任讲师

1995.1. - 2000.8. 在清华大学自动化系任副教授

2000.9. - 现在 在清华大学自动化系任教授

IEEE Fellow

模式识别，人工智能，机器学习，计算机视觉等

深度学习，小样本学习，因果学习，大模型推理等

编著书籍

1. 张长水，人工智能的底层逻辑，清华大学出版社，2024,10, 北京（科普性质的技术书，适合非人工智能专业的学者，工程技术人员，管理人员，学生学习。）

2. 张长水，人工智能引论，清华大学出版社，2024, 7, 北京（人工智能入门教材，适合初学者）

3. 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

发表文章

International Journal

• Jiang Lu, Changming Xiao, and Changshui Zhang. Meta-Modulation: A General Learning Framework for Cross-Task Adaptation. IEEE Transactions on Neural Networks and Learning Systems (TNNLS). 2024.

• Ziang Li*, Yiwen Guo*, Haodi Liu, and Changshui Zhang. A Theoretical View of Linear Backpropagation and Its Convergence. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2024.

• Ruixin Hong, Xinyu Pang, Changshui Zhang. Advances in Reasoning by Prompting Large Language Models: A Survey. Cybernetics and Intelligence. Tsinghua University Press. 2023.

• Sen Cui, Weishen Pan, Changshui Zhang* and Fei Wang*. Bipartite Ranking Fairness through a Model Agnostic Ordering Adjustment. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2023.

• Hu, Wenzheng; Che, Zhengping; Liu, Ning; Li, Mingyang; Tang, Jian; Zhang, Changshui; Wang, Jianqiang. CATRO: Channel Pruning via Class-Aware Trace Ratio Optimization. IEEE Transactions on Neural Networks and Learning Systems. 2023.

• Jiang Lu, Pinghua Gong, Jieping Ye, Jianwei Zhang, Changshui Zhang. A Survey on Machine Learning from Few Samples. Pattern Recognition. 2023.

• Changming Xiao, Qi Yang, Xiaoqiang Xu, Jianwei Zhang, Feng Zhou, Changshui Zhang. Where You Edit is What You Get: Text-Guided Image Editing with Region-Based Attention. Pattern Recognition. 2023.

• Yiwen Sun, Wenzheng Hu, Donghua Zhou, Baichuan Mo, Kun Fu, Zhengping Che, Zheng Wang, Shenhao Wang, Jinhua Zhao, Jieping Ye, Jian Tang, Changshui Zhang. Alleviating Data Sparsity Problems in Estimated Time of Arrival via Auxiliary Metric Learning. IEEE Transactions on Intelligent Transportation Systems. 2022.

• Ruixin Hong, Hongming Zhang, Xintong Yu, Changshui Zhang. Learning Event Extraction From a Few Guideline Examples. IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP). 2022.

• Zhilong Liang, Zhiwei Li, Shuo Zhou, Yiwen Sun, Jinying Yuan, Changshui Zhang. Machine-learning exploration of polymer compatibility. Cell Reports Physical Science. Vol 3, Issue 6, 2022, 10093.

• Lei Li, Wenzheng Hu, Jiang Lu, Changshui Zhang. Leaf Vein Segmentation with Self-Supervision. Computer and Electronics in Agriculture. 2022.

• Nie, Feiping; Chen, Hong; Xiang, Shiming; Zhang, Changshui; Yan, Shuicheng; Li, Xuelong. On the Equivalence of Linear Discriminant Analysis and Least Squares Regression. IEEE Transactions on Neural Networks and Learning Systems. 2022.

• Xintong Yu, Hongming Zhang, Ruixin Hong, Yangqiu Song, Changshui Zhang. VD-PCR: Improving visual dialog with pronoun coreference resolution. Pattern Recognition. 2022.

• Lili Zhu*, Zhong Cao*, Shiyao Wang, Changshui Zhang, Lei Fang, Yanhong Ren, Bingbing Xie, Jing Geng, Sheng Xie, Ling Zhao, Li Huaping Dai, Chen Wang. Single-Cell Transcriptomics Reveals Peripheral Immune Responses in Anti-Synthetase Syndrome-Associated Interstitial Lung Disease. Frontiers in Immunology. Volume 13, 2022.

• Wenzheng Hu, Mingyang Li, Zheng Wang, Jianqiang Wang and Changshui Zhang. DiFNet: Densely High-Frequency Convolutional Neural Networks. IEEE Signal Processing Letters. vol. 28, pp. 1340-1344. 2021.

• Yiwen Sun, Kun Fu, Zheng Wang, Donghua Zhou, Kailun Wu, Jieping Ye, Changshui Zhang. CoDriver ETA: Combine Driver Information in Estimated Time of Arrival by Driving Style Learning Auxiliary Task. IEEE Transactions on Intelligent Transportation Systems. vol. 23, no. 5, pp. 4037-4048. 2022.

• Jiang Lu, Lei Li, and Changshui Zhang. Self-reinforcing Unsupervised Matching. IEEE Transactions on Pattern Analysis and Machine Intelligence (2021).

• Zhong Cao, Sen Cui, Changshui Zhang. DCR: Disentangled component representation for sketch generation Pattern Recognition Letters. vol. 145, pp. 16-22. 2021.

• Yiwen Guo, Ming Lu, Wangmeng Zuo, Changshui Zhang, Yurong Chen. Deep Likelihood Network for Image Restoration with Multiple Degradation Levels. IEEE Transactions on Image Processing. vol. 30, pp. 2669-2681. 2021.

• Jian Liang, Ziqi Liu, Jiayu Zhou, Xiaoqian Jiang, Changshui Zhang and Fei Wang. Model-Protected Multi-Task Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. vol. 44, no. 2, pp. 1002-1019. 2022.

• Yiwen Guo, Long Chen, Yurong Chen, and Changshui Zhang. On Connections between Regularizations for Improving DNN Robustness. IEEE Transactions on Pattern Analysis and Machine Intelligence. vol. 43, no. 12, pp. 4469-4476, 2021.

• Zhong Cao, Jiang Lu, Sen Cui and Changshui Zhang. Zero-Shot Handwritten Chinese Character Recognition with Hierarchical Decomposition Embedding. Pattern Recognition. vol. 107, Nov. 2020.

• 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. vol. 3, no. 4, pp. 1433-1447. Apr. 2020.

• Runpeng Cui, Zhong Cao, Weishen Pan, Changshui Zhang, Jianqiang Wang. Deep Gesture Video Generation with Learning on Regions of Interest. IEEE Transactions on Multimedia. vol. 22, no. 10, pp. 2551-2563. Oct. 2020.

• Kailun Wu, Yiwen Guo, and Changshui Zhang. Compressing Deep Neural Networks with Sparse Matrix Factorization. IEEE Transactions on Neural Networks and Learning Systems. vol. 31, no. 10, pp. 3828-3838, Oct. 2020

• Ziang Yan, Yiwen Guo, Changshui Zhang. Adversarial Margin Maximization Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence. vol. 43, no. 4, pp. 1129-1139. Apr. 2021. 

• 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.

• Nan Jiang, Sheng Jin, Changshui Zhang. Hierarchical automatic curriculum learning: Converting a sparse reward navigation task into dense reward. Neurocomputing vol. 360, pp. 265-278. Sep. 2019.

• 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. vol. 31, no. 9, pp. 3215-3229, Sept. 2019.

• 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.

• 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

• 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

• 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

• 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.

• 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.

• 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.

• 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.

• 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

• 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.

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

• 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.

• 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

• 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

• 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

• 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

• 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.

• 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

• 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.

• 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

• 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.

• 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.

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

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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

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

• 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

• 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

• 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.

• 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

• 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.

• 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.

• 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)

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

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

• 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.

• 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.

• 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

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

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

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

• 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.

• 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.

• 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.

• 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.

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

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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, .

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.
  

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

• 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.
  

• 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.
  

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

• 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.

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

• 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.

• 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.

• 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.

• 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.

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

• 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.

• 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.

• 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.

• 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.

• 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.

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

• 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.

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

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

• 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.

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

• 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.

• 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.

• 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.

• 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.

• 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.

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

• 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.

• 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.

• 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.

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

• 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.

• 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.

• 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.

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

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

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

• 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.

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

• 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.

• 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.

• 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.

• 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

2024

• Kunda Yan*, Sen Cui*, Abudukelimu Wuerkaixi, Jingfeng Zhang, Bo Han, Gang Niu, Masashi Sugiyama and Changshui Zhang. Balancing Similarity and Complementarity for Federated Learning. Proceedings of the 41th International Conference on Machine Learning (ICML). 2024.

• Ruixin Hong, Hongming Zhang, Xiaoman Pan, Dong Yu and Changshui Zhang. Abstraction-of-Thought Makes Language Model Better Reasoner. In Proceedings of the 2024 Conference of the Empirical Methods in Natural Language Processing (EMNLP Findings). 2024.

• Ruixin Hong, Hongming Zhang, Xinyu Pang, Dong Yu and Changshui Zhang. A Closer Look at the Self-Verification Abilities of Large Language Models in Logical Reasoning. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). 2024.

• Yinya Huang*, Ruixin Hong*, Hongming Zhang, Wei Shao, Zhicheng Yang, Dong Yu, Changshui Zhang, Xiaodan Liang and Linqi Song. CLoMo: Counterfactual Logical Modification with Large Language Models. In Proceedings of the 2024 Conference of the Annual Meeting of the Association for Computational Linguistics (ACL). 2024.

• Ziang Li, Kailun Wu, Yiwen Guo, and Changshui Zhang. Learned ISTA with Error-based Thresholding for Adaptive Sparse Coding. 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2024.

• Sen Cui*, Abudukelimu Wuerkaixi*, Weishen Pan, Jian Liang, Lei Fang, Changshui Zhang, and Fei Wang. CLAP: Collaborative Adaptation for Checkerboard Learning. The Eleventh International Conference on Learning Representations (ICLR). 2024.

• Abudukelimu Wuerkaixi*, Sen Cui*, Jingfeng Zhang*, Kunda Yan, Bo Han, Gang Niu, Lei Fang, Changshui Zhang, and Masashi Sugiyama. Accurate Forgetting for Heterogeneous Federated Continual Learning. The Eleventh International Conference on Learning Representations (ICLR). 2024.

2023

• Ruixin Hong, Hongming Zhang, Hong Zhao, Dong Yu and Changshui Zhang. Faithful Question Answering with Monte-Carlo Planning. Proceedings of the 61th Annual Meeting of the Association for Computational Linguistics (ACL). 2023.

2022

• Abudukelimu Wuerkaixi, Kunda Yan, You Zhang, Zhiyao Duan and Changshui Zhang. DyViSE: Dynamic Vision-Guided Speaker Embedding for Audio-Visual Speaker Diarization. IEEE 24th International Workshop on Multimedia Signal Processing (MMSP). 2022.

• Sen Cui*, Jingfeng Zhang*, Jian Liang, Bo Han, Masashi Sugiyama, Changshui Zhang. Synergy-of-Experts: Collaborate to Improve Adversarial Robustness. The 36th Conference on Neural Information Processing Systems (NeurIPS2022). New Orleans, the USA, November 28th to December 9th, 2022.

• Haipeng Zhang, Changshui Zhang, Yulu Wang, Keying Zhang, Ruidong Liu, Lei Fang, Fangfang Wu, Chunmei Cao. EEG-based Assessment of Human Endurance: Association between Endurance and Brain-wave Activity. Proceedings of 2022 IEEE 5th International Conference on Artifcial Intelligence and Big Data.

• Sen Cui, Jian Liang, Weishen Pan, Kun Chen, Changshui Zhang, Fei Wang. Collaboration Equilibrium in Federated Learning. The 28th ACM SIGKDD conference on Knowledge Discovery and Data Mining (KDD). August 14-18th, 2022, Washington D.C., USA.

• Ruixin Hong, Hongming Zhang, Xintong Yu, Changshui Zhang. METGEN: A Module-based Entailment Tree Generation Framework for Answer Explanation. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics Findings (NAACL Findings). 2022.

• Wang, Yulu, Yiwen Sun, Fang Lei and Changshui Zhang. Leveraging Sparse Coding for EEG Based Emotion Recognition in Shooting. ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE. 2022.

• Hongyan Xu, Xiu Su, Shan You, Tao Huang, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu, Dadong Wang, Arcot Sowmya. Data Agnostic Filter Gating for Efficient Deep Networks. ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE. 2022.

2021

• Mingkai Zheng, Fei Wang, Shan You, Chen Qian, Changshui Zhang, Xiaogang Wang, Chang Xu. Weakly Supervised Contrastive Learning. International Conference on Computer Vision (ICCV). 2021.

• Yuru Song, Zan Lou, Shan You, Erkun Yang, Fei Wang, Chen Qian, Changshui Zhang, Xiaogang Wang. Learning with Privileged Tasks. International Conference on Computer Vision (ICCV). 2021.

• Mingkai Zheng, Shan You, Fei Wang, Chen Qian, Changshui Zhang, Xiaogang Wang, Chang Xu. ReSSL: Relational Self-Supervised Learning with Weak Augmentation. The 35th Conference on Neural Information Processing Systems (NeurIPS). Sydney, Australia, December 6-14, 2021.

• Sen Cui, Weishen Pan, Jian Liang, Changshui Zhang, Fei Wang. Addressing Algorithmic Disparity and Performance Inconsistency in Federated Learning. The 35th Conference on Neural Information Processing Systems (NeurIPS2021). Sydney, Australia, December 6-14, 2021.

• Xintong Yu, Hongming Zhang, Yangqiu Song, Changshui Zhang, Kun Xu and Dong Yu. Exophoric Pronoun Resolution in Dialogues with Topic Regularization. Conference on Empirical Methods in Natural Language Processing (EMNLP). Punta Cana, Dominican Republic, 2021. 

• Abudukelimu Wuerkaixi, Christodoulos Benetatos, Zhiyao Duan, Changshui Zhang. CollageNet: Fusing Arbitrary Melody and Accompanyment into A Coherent Song. Proceedings of the 21th International Society for Music Information Retrieval Conference (ISMIR). 2021.

• Xiu Su*, Shan You*, Mingkai Zheng, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu. K-shot NAS: Learnable Weight-Sharing for NAS with K-shot Supernets. The 38th International Conference on Machine Learning (ICML). Jul 18-24, 2021

• Xiu Su, Tao Huang, Yanxi Li, Shan You, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu. Prioritized Architecture Sampling with Monto-Carlo Tree Search. CVPR 2021. Jun 19-25, 2021.

• Xiu Su, Shan You, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu. BCNet: Searching for Network Width with Bilaterally Coupled Network. CVPR 2021. Jun 19-25, 2021.

• Weishen Pan, Sen Cui, Jiang Bian, Changshui Zhang, Fei Wang. Explaining Algorithmic Fairness Through Fairness-Aware Causal Path Decomposition. The 27th ACM SIGKDD conference on Knowledge Discovery and Data Mining (KDD). August 14-18th, 2021 Singapore, Singapore. (Oral paper)

• Sen Cui*, Weishen Pan*, Changshui Zhang, Fei Wang. Towards Model-Agnostic Post-Hoc Adjustment for Balancing Ranking Fairness and Algorithm Utility. The 27th ACM SIGKDD conference on Knowledge Discovery and Data Mining (KDD). August 14-18th, 2021 Singapore, Singapore. (Oral paper)

• Yiwen Sun, Yulu Wang, Kun Fu, Zheng Wang, Ziang Yan, Changshui Zhang, Jieping Ye. FMA-ETA: Estimating Travel Time Entirely Based on FFN With Attention. The 46th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). June, 6-11, 2021

• Xiu Su, Shan You, Tao Huang, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu. Locally Free Weight sharing for Network Width Search. The Ninth International Conference on Learning Representations (ICLR). May 4-8, 2021

• Ziang Yan, Yiwen Guo, Jian Liang, Changshui Zhang. Policy-Driven Attack: Learning to Query for Hard-label Black-box Adversarial Examples. The Ninth International Conference on Learning Representations (ICLR). May 4-8, 2021

• Yiwen Sun, Kun Fu, Zheng Wang, Changshui Zhang, and Jieping Ye. Road Network Metric Learning for Estimated Time of Arrival. The 25th International Conference on Pattern Recognition (ICPR). Milan, Italy, 10-15 January, 2021.

• Yiwen Sun, Yulu Wang, Kun Fu, Zheng Wang, Changshui Zhang, and Jieping Ye. Constructing Geographic and Long-term Temporal Graph for Traffic Forecasting. The 25th International Conference on Pattern Recognition (ICPR). Milan, Italy, 10-15 January, 2021.

详见：https://bigeye.au.tsinghua.edu.cn/paperlist.html