Zhao Kang

Zhao Kang

Resume(个人简介

Kang Zhao, master’s tutor, graduated from the Computer Science Department of Southern Illinois University in May 2017. In July 2017, he joined the University of Electronic Science and Technology. Member of the Expert Committee of Artificial Intelligence and Pattern Recognition of the Chinese Computer Society, member of the Machine Learning Committee of the Chinese Artificial Intelligence Society.

Over the past five years, he has published more than 40 papers in international top conferences and journals in the fields of artificial intelligence, pattern recognition, information retrieval and data mining, including AAAI, IJCAI, ICDE, CVPR, SIGKDD, ICDM, SDM, CIKM, IEEE Trans on Cybernetics. ACM TIST, ACM TKDD, Neurocomputing, Knowledge-Based Systems, Pattern Recognition, etc. He has been invited as a reviewer of the top journals in related fields (such as IEEE Trans on Cybernetics, IEEE TNNLS) and members of the program committees (such as AAAI, IJCAI, ACM MM, ICDM), and was awarded the excellent reviewer of IJCAI 2018. I welcome all of you to take my postgraduate exam with the journal. I also welcome undergraduate students who want to get research training and publish papers. At present, many undergraduates have cooperated with me.

Papers

The code is available on the Homepage and Google Scholar

43: Partition Level Multiview Subspace Clustering, Zhao Kang; Xinjia Zhao; Chong Peng; Hongyuan Zhu; Joey Tianyi Zhou; Xi Peng; Wenyu Chen; Zenglin Xu, Neural Networks, 2019. (JCR一区,影响因子9.86) (Xinjia Zhao为本科生)

42: Single Image Dehazing via Compositional Adversarial Network, Hongyuan Zhu, Yi Cheng, Xi Peng, Joey Tianyi Zhou, Zhao Kang, Shijian Lu, Zhiwen Fang, Liyuan Li, Joo-Hwee Lim, IEEE Transactions on Cybernetics, 2019. (JCR一区,影响因子11.53)

41: Multi-graph Fusion for Multi-view Spectral Clustering, Zhao Kang; Guoxin Shi; Shudong huang; Wenyu Chen; Xiaorong Pu; Joey Tianyi Zhou; Zenglin Xu, Knowledge-Based Systems, 2019. (JCR二区) (Guoxin Shi为本科生)

40: Auto-weighted Multi-view Co-clustering with Bipartite Graphs, Shudong Huang, Zenglin Xu, Ivor W. Tsang, Zhao Kang, Information Sciences 2019. (JCR二区)

39: Robust Principal Component Analysis: A Factorization-Based Approach with Linear Complexity, Chong Peng, Yongyong Chen, Zhao Kang, Chenglizhao Chen, Qiang Cheng, Information Sciences 2019. (JCR二区)

38: Latent Multi-view Semi-Supervised Classification, Xiaofan Bo, Zhao Kang, Zhitong Zhao, Wenyu Chen, Yuanzhang Su, The 11th Asian Conference on Machine Learning (ACML 2019), Nov.2019, Nagoya, Japan. (CCF C类) (Xiaofan Bo为本科生)

37: Auto-weighted multi-view clustering via deep matrix decomposition, Shudong Huang, Zhao Kang, Zenglin Xu, Pattern Recognition, Volume 97, 2020. (JCR二区)

36:Multiple Partitions Aligned Clustering, Zhao Kang, Zipeng Guo, Shudong Huang, Siying Wang, Wenyu Chen, Yuanzhang Su, Zenglin Xu, The 28th International Joint Conference on Artificial Intelligence(IJCAI-19), Aug. 2019, Macao, China. (Accept rate 17.9%) (CCF A类) (Zipeng Guo为本科生)

35: Clustering with Similarity Preserving, Zhao Kang, Honghui Xu, Boyu Wang, Hongyuan Zhu, Zenglin Xu, Neurocomputing, 2019. (JCR二区) (Honghui Xu为本科生)

34: RES-PCA: A Scalable Approach to Recovering Low-rank Matrices, C Peng, C Chen, Z Kang, J Li, Q Cheng, IEEE Conference on Computer Vision and Pattern Recognition (CVPR’2019). (Accept rate 25.2%) (CCF A类)

33: Locality-constrained group lasso coding for microvessel image classification, J Chen, S Zhou, Z Kang, Q Wen, Pattern Recognition Letters, 2019.

32: Similarity Learning via Kernel Preserving Embedding, Zhao Kang; Yiwei Lu; Yuanzhang Su; Changsheng Li; Zenglin Xu, The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), Honolulu, Hawaii, Jan. 2019. (Accept rate 16.2%) (CCF A类) (Yiwei Lu为本科生)

31: Robust Graph Learning from Noisy Data, Zhao Kang, Haiqi Pan, Steven C.H. Hoi, Zenglin Xu, IEEE Transactions on Cybernetics, 2019. (JCR一区,影响因子8.8) (Haiqi Pan为本科生)

30: Two Birds with One Stone: Iteratively Learn Facial Attributes with GANs, Dan Ma, Bin Liu, Zhao Kang, Jianke Zhu, Zenglin Xu, Neurocomputing, 2018. (JCR二区)

29: Auto-weighted Multi-view Clustering via Kernelized Graph Learning, Shudong Huang, Zhao Kang, Ivor W. Tsang, Zenglin Xu, Pattern Recognition, Volume 88, April 2019, Pages 174-184. (JCR二区)

28: Low-rank Kernel Learning for Graph-based Clustering , Zhao Kang, Liangjian Wen, Wenyu Chen, Zenglin Xu , Knowledge-Based Systems, Volume 163, 1 January 2019, Pages 510-517. (JCR二区)

27: Robust Graph Learning for Semi-Supervised Classification, Haiqi Pan, Zhao Kang , International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC 2018), Hangzhou, China. (Haiqi Pan为本科生)

26: Image Denoising via Improved Dictionary Learning with Global Structure and Local Similarity Preservations, Shuting Cai, Zhao Kang, Ming Yang, Xiaoming Xiong, Chone Peng, Mingqing Xiao, Symmetry 10 (5), 167.

25: Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification, Zhao Kang; Xiao Lu; Jinfeng Yi; Zenglin Xu, the 27th International Joint Conference on Artificial Intelligence (IJCAI-18), July. 2018, Stockholm, Sweden. (Accept rate 20.5%) (CCF A类)

24: Self-weighted Multi-View Clustering with Soft Capped Norm, Shudong Huang; Zhao Kang; Zenglin Xu, Knowledge-Based Systems, 2018.(JCR二区)

23: Integrate and Conquer: Double-Sided Two-Dimensional K-Means Via Integrating of Projection and Manifold Construction, Chong Peng; Zhao Kang; Shuting Cai; Qiang Cheng, ACM Transactions on Intelligent Systems and Technology (ACM TIST), 2018. (JCR二区)

22: Unified Spectral Clustering with Optimal Graph, Zhao Kang; Chong Peng; Qiang Cheng; Zenglin Xu, The Thirty-Second AAAI Conference on Artificial Intelligence, New Orleans, Lousiana, Feb. 2018. (Accept rate 24.5%)(CCF A类)

21: Kernel-driven Similarity Learning, Zhao Kang; Chong Peng; Qiang Cheng, Neurocomputing, Elsevier, 2017. (JCR二区)

20: Exploiting Nonlinear Relationships for Top-N Recommender Systems, Zhao Kang; Chong Peng; Ming Yang, Qiang Cheng, The 8th IEEE International Conference on Big Knowledge, Hefei, China, August. 2017.

19: On identifiability of 3-tensors of multilinear rank (1, Lr, Lr), Ming Yang, DunRen Che, Wen Liu, Zhao Kang, Chong Peng, Mingqing Xiao, Qiang Cheng, Big Data and Information Analytics (BDIA), American Institute of Mathematical Sciences, Vol. 1, no. 4, October 2016.

18: Image Projection Ridge Regression for Subspace Clustering, Chong Peng; Zhao Kang; Fei Xu; Yongyong Chen; Qiang Cheng, IEEE Signal Processing Letters (IEEE SPL), 2017.

17: Subspace Clustering via Variance Regularized Ridge Regression, Chong Peng; Zhao Kang; Qiang Cheng, The Thirtieth IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2017), Honolulu, Hawaii, July, 2017. (Accept rate 29%)(CCF A类)

16: Integrating Feature and Graph Learning with Low-Rank Representation, Chong Peng; Zhao Kang; Qiang Cheng, Neurocomputing, 2017. (JCR二区)

15: Clustering with Adaptive Manifold Structure Learning, Zhao Kang; Chong Peng; Qiang Cheng, The 33rd IEEE International Conference on Data Engineering (ICDE 2017), San Diego, USA, April. 2017. (Accept rate 28.9%)(CCF A类)

14: Twin Learning for Similarity and Clustering: A Unified Kernel Approach, Zhao Kang; Chong Peng; Qiang Cheng, The Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), San Francisco, California USA, Feb. 2017. (Accept rate 24.6%)(CCF A类)

13: Robust Graph Regularized Nonnegative Matrix Factorization for Clustering, Chong Peng; Zhao Kang; Yunhong Hu; Qiang Cheng, ACM Transactions on Knowledge Discovery from Data (ACM TKDD), Volume 11 Issue 3, Article No. 33, March 2017. (CCF B类)

12: A Fast Factorization-based Approach to Robust Principal Component Analysis, Chong Peng; Zhao Kang; Qiang Cheng, The IEEE International Conference on Data Mining series (ICDM 2016), Barcelona, Spain, Dec. 2016. (Accept rate 19.6%)(CCF B类)

11: Nonnegative Matrix Factorization with Integrated Graph and Feature Learning, Chong Peng; Zhao Kang; Yunhong Hu; Qiang Cheng, ACM Transactions on Intelligent Systems and Technology (ACM TIST), Vol. 8, No. 3, Article 42, February 2017. (JCR二区)

10: Top-N Recommendation on Graphs, Zhao Kang; Chong Peng; Ming Yang, Qiang Cheng, The 25th ACM Int. Conf. on Information and Knowledge Management (CIKM 2016), Indianapolis, United States, Oct. 2016. (Accept rate 23.2%)(CCF B类)

9: RAP: Scalable RPCA for Low-rank Matrix Recovery, Chong Peng; Zhao Kang; Ming Yang, Qiang Cheng, The 25th ACM Int. Conf. on Information and Knowledge Management (CIKM 2016), Indianapolis, United States, Oct. 2016. (Accept rate 23.2%)(CCF B类)

8: Feature Selection Embedded Subspace Clustering, Chong Peng; Zhao Kang; Ming Yang, Qiang Cheng, IEEE Signal Processing Letters (IEEE SPL) 23(7), 1018-1022, 2016.

7: Top-N recommendation with novel rank approximation, Zhao Kang and Qiang Cheng, 2016 SIAM Int. Conf. on Data Mining (SDM 2016), Miami, FL, May. 2016. (Accept rate 26%)(CCF B类)

6: Top-N Recommender System via Matrix Completion, Zhao Kang, Chong Peng, and Qiang Cheng, The Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, Arizona, USA, Feb. 2016. (Accept rate 26%)(CCF A类)

5: Robust PCA Via Nonconvex Rank Approximation, Zhao Kang, Chong Peng, and Qiang Cheng, The IEEE International Conference on Data Mining series (ICDM 2015), Atlantic, NJ, USA, Nov. 2015. (Accept rate 68/807=8.4%)(CCF B类)

4: Robust Subspace Clustering via Tighter Rank Approximation, Zhao Kang, Chong Peng, and Qiang Cheng, The 24th ACM Int. Conf. on Information and Knowledge Management (CIKM 2015), Melbourne, Australia, Oct. 2015. (Accept rate 17.98%)(CCF B类)

3: Subspace clustering using log-determinant rank approximation, Chong Peng, Zhao Kang, Huiqing Li, Qiang Cheng, The 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015), Sydney, Australia, Aug. 2015. (Accept rate 19.4%)(CCF A类)

2: Robust Subspace Clustering via Smoothed Rank Approximation , Zhao Kang, Chong Peng, and Qiang Cheng, IEEE Signal Processing Letters (IEEE SPL) 22 (11), 2088-2092.

1: LogDet Rank Minimization with Application to Subspace Clustering, Zhao Kang, Chong Peng, Jie Cheng and Qiang Cheng, Computational Intelligence and Neuroscience, Volume 2015 (2015).

Research project

2: 2019.1-2021.12,Similarity Learning and Application Research of Complex Structure Data(No. 61806045), China Natural Science Youth Fund,260000,Hosting.

1: 2018.1-2019.12,Low-dimensional structure learning of high-dimensional data(No.ZYGX2017KYQD177) Central University Basic Research Service Fees,150000,Hosting.

Professional Activities

Academic conference organization member

Member of the special committee on artificial intelligence and pattern recognition of the Chinese computer society

Member of machine learning special committee of Chinese association for artificial intelligence

Member of China computer society

AAAI member

Program Committee Member

CVPR 2020, ECAI 2020, AAAI2020, ICCV 2019, CIKM 2019, IJCAI 2019, ACM MM 2019, AAAI 2019, ICDM 2018, ACM MM 2018, IJCAI 2018, AAAI 2018

Reviewer

IIEEE Transactions on Cybernetics

IEEE Transactions on Knowledge and Data Engineering (TKDE)

IEEE Transactions on Systems, Man, and Cybernetics

IEEE Transactions on Neural Networks and Learning Systems

Knowledge-based Systems

Information Sciences

Neurocomputing

IEEE Access

Engineering Applications of Artificial Intelligence

Pattern Recognition Letters

Contact

E-mail

zkang@uestc.edu.cn