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姓      名张召    性      别        男

     

出生年月
    最终学位博士
毕业学校香港城市大学 (City University of Hong Kong)
从事专业数据挖掘与机器学习,图像处理与模式识别
    职      务博导、硕导
所属院系365bet手机版网址(人工智能学院)
 所属科室     (研究所)多媒体计算研究所
    职      称      教授
 联系方式
办公     电话:
Email: cszzhang@gmail.com
通讯     地址: 安徽省合肥市蜀山区丹霞路485号(365bet手机版网址翡翠湖校区),365bet手机版网址
邮编: 230601
简    历

张 召,男,博士,365bet手机版网址“黄山学者”特聘教授,博士生导师,IEEE高级会员/CCF高级会员。2013年7月博士毕业于香港城市大学 (博士导师:Prof. Tommy W.S. Chow, IEEE Fellow),2012年2-5月在新加坡国立大学进行访问研究 (指导教授:颜水成,IEEE Fellow/IAPR Fellow,新加坡国家工程院院士),同年9-12月在中科院自动化所模式识别国家重点实验室进行访问研究 (指导教授:刘成林,IEEE Fellow/IAPR Fellow,国家重点实验室主任)。

      目前,主要从事机器学习与数据挖掘、模式识别与图像处理方向的研究,已发表学术期刊和会议论文70余篇,其中包括32篇IEEE/ACM Trans长文(一作或通讯25篇)、34篇CCF-A类或SCI一区顶级期刊论文(一作或通讯25篇)、16篇CCF推荐A/B类权威国际会议长文(一作或通讯15篇)。主持国家自然基金项目3项、安徽省杰出青年科学基金项目、江苏省“六大人才高峰”高层次人才项目、江苏省高校自然科学研究重大项目等;已获授权国家发明专利19项、软著15项;获2014年江苏省科学技术二等奖、2015年江苏省计算机学会青年科技奖、2016年ACM中国新星奖Honorable Mention等;获2017年江苏省“青蓝工程”优秀青年骨干教师培养对象、2018年江苏省优秀硕士学位论文指导教师等荣誉称号。

      在专业领域活动方面,担任CCF人工智能与模式识别专委会委员、CAAI机器学习专委会委员、CAA模式识别与机器智能专委会委员等;现/曾担任IEEE Transactions on Image Processing (CCF-A类顶级期刊) 、Elsevier Signal Processing等国际SCI期刊的编委(AE),以及Journal of Visual Communication and Image Representation、Image and Vision Computing等的执行客座编委(Managing GE);现/曾担任国际权威学术会议IJCAI、SDM、ECAI、BMVC和PAKDD等的高级程序委员(SPC)或领域主席(AC),以及顶级会议KDD、ICDM、ACM MM、IJCAI、AAAI、CVPR、ICCV和ECCV等的程序委员(PC);长期受邀担任IEEE/ACM Trans、ACM Computing Surveys和IJCV等顶级学术期刊的审稿人。



详细个人信息请参见个人主页:https://sites.google.com/site/cszzhang


研究方向

数据挖掘与机器学习、模式识别与图像处理。具体包括:(1)表示学习(如特征提取、稀疏表示与字典学习、低秩表示与复原、深度表示学习),(2)半监督分类与深度半监督学习及其在底层视觉任务(如图像恢复、去噪、增强和描述)和高级视觉任务(如图像分类、聚类、目标检测和识别)中的应用研究。

教学与人才培养工作

1. 目前已指导博士生3名(含硕博生2名)、硕士生9名(其中7人已毕业)。

2. 指导硕士生获学业奖学金特等奖6次、1名博士生获国家奖学金、3名硕士生获国家奖学金、2名硕士生获校级研究生学术标兵、6名硕士生获校级优秀毕业生。

3. 指导1名硕士生获省优秀硕士学位论文、2名硕士生获省研究生创新工程项目(省立省助)。



  • Recruiting: I am always looking for self-motivated Master and PhD students to do cutting edge research on data mining & machine learning, image processing & computer vision. If interested, please email your full CV to me for consideration (E-mail: cszzhang@gmail.com).

  • 博士和硕士招生说明主要研究方向:数据挖掘与机器学习、图像处理与计算机视觉。欢迎有志从事科研、勇于挑战、有责任心的同学报考!读研和读博期间表现优秀者,将额外提供科研补贴并优先考虑海内外学术交流(全额资助)。态度和责任心决定高度,效率决定成败!

  • (1) 欢迎校内外推免研究生和校内优秀本科生申请加入实验室从事科研!(2) 对于博士生、硕士生和优秀本科生,分别提供5万元、3万元和1万元的科研经费使用权。

  • 特别说明发送E-mail时,邮件主题请按照如下格式:“20XX年博士或硕士导师申请-姓名-硕士与本科学校名称”,邮件内容需体现个人研究经历、成果、英语水平和预期目标等.  Due to limited quota, only shortlisted candidates will be notified. 




学术与社会服务


主要论著



The fol?low?ings are the statistics of selected pub?li?ca?tions (60 journal articles + 26 conference papers) that are au?thored/coau?thored by our team mem?bers, including

Journals: 32 IEEE/ACM Transactions(6 IEEE TIP, 6 IEEE TKDE, 10 IEEE TNNLS, 2 IEEE TCYB, IEEE TSP, IEEE TCSVT, IEEE TMM, IEEE TBD, 2 IEEE TII, ACM TOMM, ACM TIST), 7 Pattern Recognition, 8 Neural Networks, IEEE Multimedia Magazine, Computer Vision and Image Understanding, Information Sciences, 3 Neurocomputing, 2 IEEE Signal Processing Letters, etc.  

Conferences: 3 IJCAI, 2 ACM Multimedia, 4 ICDM, 3 ECAI, SDM, ICASSP, ICMR, 6 ICPR, ICIP, PRICAI, 3 PCM, etc. 

*indicates the Corresponding Author

Access full publications in Google Scholar and DBLP. Some representative publications are below: 

[Representative Publications]  (Sorted by formal publication year) 

   [2020]:  


  • Zhao Zhang, Yulin Sun, Yang Wang*, Zheng Zhang, Haijun Zhang, Guangcan Liu and Meng Wang, Twin-Incoherent Self-Expressive Locality-Adaptive Latent Dictionary Pair Learning for Classification, IEEE Transactions on Neural Networks and Learning Systems(IEEE TNNLS), Mar 2020.    PDF

  • Zhao Zhang*, Yan Zhang, Guangcan Liu, Jinhui Tang, Shuicheng Yan and Meng Wang, Joint Label Prediction based Semi-Supervised Adaptive Concept Factorization for Robust Data Representation, IEEE Transactions on Knowledge and Data Engineering(IEEE TKDE), vol.32, no.5, pp.952-970, May 2020.    PDF

  • Jiahuan Ren, Zhao Zhang*, Sheng Li, Yang Wang, Guangcan Liu, Shuicheng Yan and Meng Wang, Learning Hybrid Representation by Robust Dictionary Learning in Factorized Compressed Space, IEEE Transactions on Image Processing(IEEE TIP), vol.29, no.1, pp.3941-3956, Dec 2020.    PDF

  • Ximing Li, Yang Wang*, Zhao Zhang*, Richang Hong, Zhuo Li and Meng Wang, RMoR-Aion: Robust Multioutput Regression by Simultaneously Alleviating Input and Output Noises, IEEE Transactions on Neural Networks and Learning Systems(IEEE TNNLS), Mar 2020.    PDF

  • Huibing Wang, Yang Wang*, Zhao Zhang*, Xianping Fu, Meng Wang, Kernelized Multiview Subspace Analysis by Self-weighted Learning, IEEE Transactions on Multimedia(IEEE TMM), May 2020.   

  • Xinjian Gao, Zhao Zhang*, Tingting Mu, Xudong Zhang, Chaoran Cui and Meng Wang, Self-attention Driven Adversarial Similarity Learning Network, Pattern Recognition(PR), Mar 2020.   PDF

  • Jie Wen, Zheng Zhang*, Zhao Zhang, Lunke Fei and Meng Wang, Generalized Incomplete Multi-view Clustering With Flexible Locality Structure Diffusion, IEEE Transactions on Cybernetics(IEEE TCYB), Mar 2020.     PDF

  • Zhengming Li, Zheng Zhang, Jie Qin, Zhao Zhang and Ling Shao, Discriminative Fisher Embedding Dictionary Learning Algorithm for Object Recognition, IEEE Transactions on Neural Networks and Learning Systems(IEEE TNNLS), vol.31, no.3, pp.786-800, Mar 2020.     PDF

  • Rui Gao, Xingsong Hou, Jie Qin, Jiaxin Chen, Li Liu, Fan Zhu, Zhao Zhang and Ling Shao, Zero-VAE-GAN: Generating Unseen Features for Generalized and Transductive Zero-Shot Learning, IEEE Transactions on Image Processing (IEEE TIP), vol.29, no.1, pp.3665-3680, Dec 2020.    PDF

  • Zhao Zhang*, Jiahuan Ren, Zheng Zhang* and Guangcan Liu, Deep Latent Low-Rank Fusion Network for Progressive Subspace Discovery, In: Proceedings of the 29th International Joint Conferences on Artificial Intelligence(IJCAI), Yokohama, Japan, April 2020.    PDF (Acceptance rate: 12.6%)

  • Jinjia Peng, Yang Wang*, Huibing Wang, Zhao Zhang*, Xianping Fu* and Meng Wang, Unsupervised Vehicle Re-identification with Progressive Adaptation, In: Proceedings of the 29th International Joint Conference on Artificial Intelligence(IJCAI), Yokohama, Japan, April 2020.    PDF(Acceptance rate: 12.6%)

  • Zhao Zhang*, Zemin Tang, Zheng Zhang, Yang Wang, Jie Qin and Meng Wang, Fully-Convolutional Intensive Feature Flow Neural Network for Text Recognition,  In: Proceedings of the 24th European Conference on Artificial Intelligence (ECAI), Santiago de Compostela, June 2020.    PDF

  • Zhao Zhang*, Yulin Sun, Yang Wang, Zhengjun Zha, Shuicheng Yan and Meng Wang, Convolutional Dictionary Pair Learning Network for Image Representation Learning, In: Proceedings of the 24th European Conference on Artificial Intelligence (ECAI), Santiago de Compostela, June 2020.    PDF

  • Xianzhen Li, Zhao Zhang*, Yang Wang, Guangcan Liu, Shuicheng Yan and Meng Wang, Multilayer Collaborative Low-Rank Coding Network for Robust Deep Subspace Discovery, In: Proceedings of the 24th European Conference on Artificial Intelligence (ECAI), Santiago de Compostela, June 2020.    PDF

   [2019]:  


  • Zhao Zhang*, Yan Zhang, Sheng Li, Guangcan Liu, Dan Zeng, Shuicheng Yan and Meng Wang, Flexible Auto-weighted Local-coordinate Concept Factorization: A Robust Framework for Unsupervised Clustering, IEEE Transactions on Knowledge and Data Engineering(IEEE TKDE), Sep 2019.    PDF

  • Zhao Zhang*, Jiahuan Ren, Weiming Jiang, Zheng Zhang, Richang Hong, Shuicheng Yan and Meng Wang, Joint Subspace Recovery and Enhanced Locality Driven Robust Flexible Discriminative Dictionary Learning, IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT), June 2019.    PDF

  • Zhao Zhang*, Lei Jia, Mingbo Zhao, Guangcan Liu, Meng Wang and Shuicheng Yan, Kernel-Induced Label Propagation by Mapping for Semi-Supervised Classification, IEEE Transactions on Big Data(IEEE TBD), vol.5, no.2, pp.148-165, June 2019.    PDF

  • Huan Zhang, Zhao Zhang*, Mingbo Zhao, Qiaolin Ye, Min Zhang and Meng Wang, Robust Triple-Matrix-Recovery-Based Auto-Weighted Label Propagation for Classification, IEEE Transactions on Neural Networks and Learning Systems(IEEE TNNLS), Nov 2019.     PDF

  • Yulin Sun, Zhao Zhang*, Weiming Jiang, Zheng Zhang, Li Zhang, Shuicheng Yan and Meng Wang, Discriminative Local Sparse Representation by Robust Adaptive Dictionary Pair Learning, IEEE Transactions on Neural Networks and Learning Systems(IEEE TNNLS), Nov 2019.    PDF

  • Yan Zhang, Zhao Zhang*, Sheng Li, Jie Qin, Guangcan Liu, Meng Wang and Shuicheng Yan, Unsupervised Nonnegative Adaptive Feature Extraction for Data Representation, IEEE Transactions on Knowledge and Data Engineering(IEEE TKDE), vol.31, no.12, pp.2423-2440, Dec 2019.   PDF

  • Guangcan Liu, Zhao Zhang, Qingshan Liu and Hongkai Xiong, Robust Subspace Clustering with Compressed Data, IEEE Transactions on Image Processing(IEEE TIP), vol.28, no.10, pp.5161-5170, Oct 2019.    PDF

  • Linlin Liu, Haijun Zhang, Xiaofei Xu, Zhao Zhang and Shuicheng Yan, Collocating Clothes with Generative Adversarial Networks Co-supervised by Categories and Attributes: A Multi-Discriminator Framework, IEEE Transactions on Neural Networks and Learning Systems(IEEE TNNLS), Sep 2019.    PDF

  • Qiaolin Ye*, Zechao Li, Liyong Fu, Zhao Zhang, Wankou Yang and Guowei Yang, Non-Peaked Discriminant Analysis for Data Representation, IEEE Transactions on Neural Networks and Learning Systems(IEEE TNNLS), vol.30, no.12, pp.3818-3832, Dec 2019.    PDF

  • Lei Wang, Bangjun Wang, Zhao Zhang*, Qiaolin Ye, Liyong Fu*, Guangcan Liu and Meng Wang, Robust Auto-weighted Projective Low-Rank and Sparse Recovery for Visual Representation, Neural Networks(NN), vol.117, pp.201-215, Sep 2019.    PDF

  • Zhao Zhang*, Jiahuan Ren, Sheng Li, Richang Hong, Zhengjun Zha and Meng Wang, Robust Subspace Discovery by Block-diagonal Adaptive Locality-constrained Representation, In: Proceedings of the 27th ACM International Conference on Multimedia(ACM MM), Nice, France, pp.1569-1577, Oct 2019.     PDFCode

  • Zhao Zhang*, Weiming Jiang, Zheng Zhang, Sheng Li, Guangcan Liu and Jie Qin, Scalable Block-Diagonal Locality-Constrained Projective Dictionary Learning, In: Proceedings of the 28th International Joint Conference on Artificial Intelligence(IJCAI), Macao, China, pp.4376-4382, Aug 2019.    (Acceptance rate: 17.9%)PDFCode

  • Yanyan Wei, Zhao Zhang*, Haijun Zhang, Richang Hong and Meng Wang, A Coarse-to-Fine Multi-stream Hybrid Deraining Network for Single Image Deraining, In: Proceedings of the 19th IEEE International Conference on Data Mining(ICDM), Beijing, China, pp.628-637, Oct 2019.    (Regular paper, Acceptance rate: 9.08%)  PDF

  • Zhao Zhang*, Lei Wang, Sheng Li, Yang Wang, Zheng Zhang, Zhengjun Zha and Meng Wang, Adaptive Structure-constrained Robust Latent Low-Rank Coding for Image Recovery, In: Proceedings of the 19th IEEE International Conference on Data Mining(ICDM), Beijing, China, pp.846-855, Oct 2019.   (Regular paper, Acceptance rate: 9.08%) PDF

  • Zhao Zhang*, Yulin Sun, Zheng Zhang, Yang Wang, Guangcan Liu and Meng Wang, Learning Structured Twin-Incoherent Twin-Projective Latent Dictionary Pairs for Classification, In: Proceedings of the 19th IEEE International Conference on Data Mining(ICDM), Beijing, China, pp.836-845, Oct 2019.   (Regular paper, Acceptance rate: 9.08%)PDFCode

  • Yan Zhang, Zhao Zhang*, Zheng Zhang, Mingbo Zhao, Li Zhang, Zhengjun Zha and Meng Wang, Deep Self-representative Concept Factorization Network for Representation Learning, In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp.361-369, Dec 2019.     PDF

  • Zhao Zhang*, Yan Zhang, Sheng Li, Guangcan Liu, Meng Wang, Shuicheng Yan, Robust Unsupervised Flexible Auto-weighted Local-Coordinate Concept Factorization for Image Clustering, In: Proceedings of the 44th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, pp.2092-2096, May 2019.   PDF


   [2018]:  


  • Zhao Zhang*, Weiming Jiang, Jie Qin, Li Zhang, Fanzhang Li, Min Zhang and Shuicheng Yan, Jointly Learning Structured Analysis Discriminative Dictionary and Analysis Multiclass Classifier, IEEE Transactions on Neural Networks and Learning Systems(IEEE TNNLS), vol.29, no.8, pp.3798-3814, August 2018.    PDFCode

  • Zhao Zhang*, Fanzhang Li, Lei Jia, Jie Qin, Li Zhang and Shuicheng Yan, Robust Adaptive Embedded Label Propagation with Weight Learning for Inductive Classification, IEEE Transactions on Neural Networks and Learning Systems(IEEE TNNLS), vol.29, no.8, pp.3388-3403, August 2018.    PDF

  • Zhao Zhang*, Lei Jia, Mingbo Zhao, Qiaolin Ye, Min Zhang and Meng Wang, Adaptive Non-Negative Projective Semi-Supervised Learning for Inductive Classification, Neural Networks(NN), vol.108, pp.128-145, Dec 2018.    PDF

  • Yan Zhang, Zhao Zhang*, Jie Qin, Li Zhang, Bing Li and Fanzhang Li, Semi-Supervised Local Multi-Manifold Isomap by Linear Embedding for Feature Extraction, Pattern Recognition(PR), vol.76, pp.662-678, April 2018.    PDF

  • Qiaolin Ye, Liyong Fu*, Zhao Zhang, Henghao Zhao and Meem Naiem, Lp- and Ls-Norm Distance Based Robust Linear Discriminant Analysis, Neural Networks(NN), vol.105, pp.393-404, Sep 2018.    PDF

  • Xiaojuan Huang, Li Zhang*, Bangjun Wang, Zhao Zhang and Fanzhang Li, Feature Weight Estimation based on Dynamic Representation and Neighbor Sparse Reconstruction, Pattern Recognition(PR), vol.81, pp.388-403, Sep 2018.    PDF

  • Lei Wang, Zhao Zhang*, Sheng Li, Guangcan Liu, Chenping Hou and Jie Qin, Similarity-Adaptive Latent Low-Rank Representation for Robust Data Representation, In: Proceedings of the 15th Pacific Rim International Conference on Artificial Intelligence(PRICAI), Nanjing, China, pp.71-84, June 2018. 

  • Zhao Zhang*, Weiming Jiang, Sheng Li, Jie Qin, Guangcan Liu, and Shuicheng Yan, Robust Locality-Constrained Label Consistent KSVD by Joint Sparse Embedding, In: Proceedings of the 24th International Conference on Pattern Recognition(ICPR), Beijing, China, April 2018. 

  • Huan Zhang, Zhao Zhang*, Sheng Li, Qiaolin Ye, Mingbo Zhao, and Meng Wang, Robust Adaptive Label Propagation by Double Matrix Decomposition, In: Proceedings of the 24th International Conference on Pattern Recognition(ICPR), Beijing, China, April 2018.  

  • Jiahuan Ren, Zhao Zhang*, Sheng Li, Guangcan Liu, Meng Wang, and Shuicheng Yan, Robust Projective Low-Rank and Sparse Representation by Robust Dictionary Learning, In: Proceedings of the 24th International Conference on Pattern Recognition(ICPR), Beijing, China, April 2018. 

  • Lei Wang, Zhao Zhang*, Guangcan Liu, Qiaolin Ye, Jie Qin, and Meng Wang, Robust Adaptive Low-Rank and Sparse Embedding for Feature Representation, In: Proceedings of the 24th International Conference on Pattern Recognition(ICPR), Beijing, China, April 2018. 

  • Yulin Sun, Zhao Zhang*, Weiming Jiang, Guangcan Liu, Meng Wang, and Shuicheng Yan, Robust Discriminative Projective Dictionary Pair Learning by Adaptive Representations, In: Proceedings of the 24th International Conference on Pattern Recognition(ICPR), Beijing, China, April 2018.

   [2017]:  


  • Zhao Zhang*, Fanzhang Li, Mingbo Zhao, Li Zhang and Shuicheng Yan, Robust Neighborhood Preserving Projection by Nuclear/L2,1-Norm Regularization for Image Feature Extraction, IEEE Transactions on Image Processing(IEEE TIP), vol.26, no.4, pp.1607-1622, April 2017.    PDF

  • Zhao Zhang*, Weiming Jiang, Fanzhang Li, Mingbo Zhao, Bing Li and Li Zhang, Structured Latent Label Consistent Dictionary Learning for Salient Machine Faults Representation based Robust Classification, IEEE Transactions on Industrial Informatics (IEEE TII), vol.13, no.2, pp.642-654, April 2017.    PDF

  • Zhao Zhang*, Yan Zhang, Fanzhang Li, Mingbo Zhao, Li Zhang and Shuicheng Yan, Discriminative Sparse Flexible Manifold Embedding with Novel Graph for Robust Visual Representation and Label Propagation, Pattern Recognition(PR), vol.61, pp.492–510, Jan 2017.    PDF

  • Zhao Zhang*, Mingbo Zhao, Fanzhang Li, Li Zhang and Shuicheng Yan, Robust Alternating Low-Rank Representation by Joint Lp- and L2,p-norm Minimization, Neural Networks(NN), vol.96, pp.55-70, Dec 2017.    PDF

  • Zhao Zhang*, Lei Jia, Min Zhang, Li Zhang, Bing Li and Fanzhang Li, Discriminative Clustering on Manifold for Adaptive Transductive Classification, Neural Networks(NN), vol.94, pp.260-273, Oct 2017.    PDF

  • Zhao Zhang*, Lei Wang, Lei Jia, Fanzhang Li, Li Zhang and Mingbo Zhao, Projective Label Propagation by Label Embedding: A Deep Label Prediction Framework for Representation and Classification, Knowledge-Based Systems(KBS), vol.119, pp.94–112, Mar 2017.    PDF

  • Zhenfeng Gu (指导的本科生), Zhao Zhang*, Jiabao Sun and Bing Li, Robust Image Recognition by L1-norm Twin-Projection Support Vector Machine, Neurocomputing(IJON), vol.223, pp.1–11, Feb 2017.    PDF

  • Tingwei Pei, Li Zhang*, Bangjun Wang, Fanzhang Li and Zhao Zhang, Decision pyramid classifier for face recognition under complex variations using single sample per person, Pattern Recognition(PR), vol.64, pp.305-313, April 2017.    PDF

   [2016]:  


  • Zhao Zhang*, Fanzhang Li, Tommy W.S. Chow, Li Zhang and Shuicheng Yan, Sparse Codes Auto-Extractor for Classification: A Joint Embedding and Dictionary Learning Framework for Representation, IEEE Transactions on Signal Processing(IEEE TSP), vol.64, no.14, pp.3790-3805, July 2016.    PDF

  • Zhao Zhang*, Fanzhang Li, Mingbo Zhao, Li Zhang and Shuicheng Yan, Joint Low-rank and Sparse Principal Feature Coding for Enhanced Robust Representation and Visual Classification, IEEE Transactions on Image Processing(IEEE TIP), vol.25, no.6, pp.2429-2443, June 2016.    PDF

  • Weiming Jiang, Zhao Zhang*, Fanzhang Li, Li Zhang, Mingbo Zhao and Xiaohang Jin, Joint Label Consistent Dictionary Learning and Adaptive Label Prediction for Semi-Supervised Machine Fault Classification, IEEE Transactions on Industrial Informatics (IEEE TII), vol.12, no.1, pp.248-256, Feb 2016.    PDF

  • Qiaolin Ye*, Jian Yang, Tongming Yin and Zhao Zhang, Can the Virtual Labels Obtained by Traditional LP Approaches Be Well Encoded in WLR? IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), vol.27, no.7, pp.1591-1598, July 2016.    PDF

  • Zhao Zhang*, Fanzhang Li, Mingbo Zhao, Li Zhang and Shuicheng Yan. Nuclear-Norm Regularized Neighborhood Preserving Projection. In: Proceedings of the 23rd International Conference on Image Processing(ICIP), Phoenix, Arizona, USA, Sep 2016. 

  • Lei Jia, Zhao Zhang*, Lei Wang, Weiming Jiang, and Mingbo Zhao. Adaptive Neighborhood Propagation by Joint L2,1-norm Regularized Sparse Coding for Representation and Classification. In: Proceedings of the 16th IEEE International Conference on Data Mining (ICDM), Barcelona, Spain, pp.201-210, Sep 2016.   (Regular paper, Acceptance rate: 8.5%)   PDF

   [2015]:  


  • Zhao Zhang*, Mingbo Zhao and Tommy W. S. Chow, Graph based Constrained Semi-Supervised Learning Framework via Label Propagation over Adaptive Neighborhood, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), vol.27, no.9, pp.2362-2376, Sep 2015.    PDF

  • Zhao Zhang*, Cheng-Lin Liu and Mingbo Zhao, A Sparse Projection and Low-Rank Recovery Framework for Handwriting Representation and Salient Stroke Feature Extraction, ACM Transactions on Intelligent Systems and Technology(ACM TIST), vol.6, no.1, pp.9:1-9:26, April 2015.    PDF

  • Zhao Zhang*, Mingbo Zhao, Bing Li, Peng Tang and Fanzhang Li, Simple Yet Effective Color Principal and Discriminant Feature Extraction for Representing and Recognizing Color Images, Neurocomputing (IJON), vol.149, pp.1058–1073, Feb 2015.    PDF

  • Zhao Zhang*, Shuicheng Yan, Mingbo Zhao and Fanzhang Li, Bilinear Low-Rank Coding Framework and Extension for Robust Image Recovery and Feature Representation, Knowledge-Based Systems(KBS), vol.86, pp.143–157, Sep 2015.     PDF

  • Yuchen Liang (指导的本科生), Zhao Zhang*, Weiming Jiang, Mingbo Zhao and Fanzhang Li, Bilinear Embedding Label Propagation: Towards Scalable Prediction of Image Labels, IEEE Signal Processing Letters (IEEE SPL), vol.22, no.12, pp.2411-2415, Oct 2015.    PDF

  • Mingbo Zhao, Tommy W. S. Chow, Zhou Wu*, Zhao Zhang and Bing Li, Learning from Normalized Local and Global Discriminative Information for Semi-Supervised Regression and Dimensionality Reduction, Information Sciences(INS), vol.423, pp.286–309, Dec 2015.    PDF

  • Mingbo Zhao, Tommy W. S. Chow, Zhao Zhang* and Bing Li, Automatic Image Annotation via Compact Graph based Semi-supervised Learning, Knowledge-Based Systems(KBS), vol.76, pp.148–165, Mar 2015.     PDF

  • Zhao Zhang*, Li Zhang, Mingbo Zhao, Weiming Jiang, Yuchen Liang and Fanzhang Li. Semi-Supervised Image Classification by Nonnegative Sparse Neighborhood Propagation. In: Proceedings of the ACM International Conference on Multimedia Retrieval (ACM ICMR), Shanghai, China, pp.139-146, June 2015.    PDF

   [2014]:  


  • Zhao Zhang*, Shuicheng Yan and Mingbo Zhao, Similarity Preserving Low-Rank Representation for Enhanced Data Representation and Effective Subspace Learning, Neural Networks (NN), vol.53, pp.81-94, May 2014.    PDF

  • Zhao Zhang* and Tommy W. S. Chow, Maximum Margin Multisurface Support Tensor Machines with Application to Image Classification and Segmentation, Expert Systems with Applications (ESWA), vol.39, iss.1, pp. 850-861, Jan 2012.     PDF

  • Mingbo Zhao, Zhao Zhang*, Tommy W. S. Chow and Bing Li, A General Soft Label based Linear Discriminant Analysis for Semi-supervised Dimension Reduction, Neural Networks (NN), vol.55, pp.83-97, July 2014.     PDF

  • Mingbo Zhao, Zhao Zhang, Tommy W. S. Chow and Bing Li*, Soft Label based Linear Discriminant Analysis for Image Recognition and Retrieval, Computer Vision and Image Understanding(CVIU), vol.121, pp.86-99, April 2014.     PDF

  • Zhao Zhang*, Fanzhang Li and Mingbo Zhao. Transformed Neighborhood Propagation. In: Proceedings of the 22nd International Conference on Pattern Recognition (ICPR), Stockholm, Sweden, pp.3792-3797, 2014. 

   [2013]:  


  • Zhao Zhang*, Shuicheng Yan and Mingbo Zhao, Pairwise Sparsity Preserving Embedding for Unsupervised Subspace Learning and Classification, IEEE Transactions on Image Processing (IEEE TIP), vol.22, iss.12, pp.4640-4651, Dec 2013.    PDF

  • Zhao Zhang*, Tommy W. S. Chow and Mingbo Zhao, M-Isomap: Orthogonal Constrained Marginal Isomap for Nonlinear Dimensionality Reduction,  IEEE Transactions on Cybernetics (IEEE TCYB), vol.43, iss.1, pp.180-192, Feb 2013.    PDF

  • Zhao Zhang*, Mingbo Zhao and Tommy W. S. Chow, Binary- and Multi-Class Group Sparse Canonical Correlation Analysis for Feature Extraction and Classification, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), vol.25, iss.10, pp.2192-2205, Oct 2013.    PDF

  • Zhao Zhang*, Tommy W. S. Chowand Mingbo Zhao, Trace Ratio Optimization based Semi-Supervised Nonlinear Dimensionality Reduction for Marginal Manifold Visualization, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), vol.25, iss.5, pp.1148-1161, May 2013.    PDF

   [Before 2012]:  


  • Zhao Zhang*, Mingbo Zhao and Tommy W. S. Chow, Marginal Semi-Supervised Sub-Manifold Projections with Informative Constraints for Dimensionality Reduction and Recognition, Neural Networks (NN), vol. 36, pp. 97-111, Dec 2012.     PDF(Errors corrected) 

  • Zhao Zhang*, Mingbo Zhao and Tommy W. S. Chow, Constrained Large Margin Local Projection Algorithms and Extensions for Multimodal Dimensionality Reduction, Pattern Recognition (PR), vol.46, iss.12, pp.4466-4493, July 2012.     PDF

  • Mingbo Zhao, Zhao Zhang and Tommy W. S. Chow*, Trace Ratio Criterion based Generalized Discriminative Learning for Semi-Supervised Dimensionality Reduction, Pattern Recognition(PR), vol.45, iss.4, pp.1482-1499, April 2012.    PDF

  • Zhao Zhang* and Tommy W. S. Chow, Robust Linearly Optimized Discriminant Analysis, Neurocomputing (IJON), vol.79, pp.140-157, March 2012.    PDF

  • Zhao Zhang* and Tommy W. S. Chow, Tensor Locally Linear Discriminative Analysis, IEEE Signal Processing Letters (IEEE SPL), vol.18, iss.11, pp.843-846, Nov 2011.    PDF(Errors corrected)



 

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