Yazhou Ren

Yazhou Ren

Resume(个人简介

Yazhou Ren, Assistant Professor and Master Advisor

He obtained his Bachelor degree in Information and Computing Science and his and his Ph.D. degree in Computer Application Technology from South China University of Technology in 2009 and 2014, respectively. He was co-trained under the supervision of Professor Carlotta Domeniconi at George Mason University from August 2012 to July 2014. He has published many papers in internationally renowned journals such as KAIS and Neurocomputing, as well as internationally renowned journals such as IJCAI, AAAI, ICDM, SDM, ECML/PKDD and IJCNN. He serves as a reviewer of TKDE, KAIS, Neurocomputing and Computational Intelligence. In January 2015, he joined the School of Computer Science and Technology, University of Electronic Science and Technology of China. His research interests include machine learning, pattern recognition and data mining, especially clustering analysis, semi-supervised learning and self-paced learning.

Google scholar

Major academic achievements and contributions

Book chapters

  1. Yazhou Ren. Big Data Clustering and Its Applications in Regional Science. In Book: Big Data for Regional Science. Edited by Laurie A Schintler and Zhenhua Chen. Routledge, 2018, Chapter 21, pages 257-264.

Conference papers

  1. Xuanwu Liu, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Yazhou Ren, Maozu Guo. Ranking-based Deep Cross-modal Hashing. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) (CCF A), 2019, Accepted.
  2. Yazhou Ren, Xiaohui Hu, Ke Shi, Guoxian Yu, Dezhong Yao, and Zenglin Xu. Semi-supervised DenPeak Clustering with Pairwise Constraints. In Proceedings of the 15th Pacific Rim International Conference on Artificial Intelligence (PRICAI) (CCF C), 2018, pages 837–850.
  3. Yazhou Ren, Xin Yan, Zechuan Hu, and Zenglin Xu. Self-Paced Multi-Task Multi-View Capped-norm Clustering. In Proceedings of the 25th International Conference on Neural Information Processing (ICONIP) (CCF C), 2018.
  4. Yuehui Wang, Maozu Guo, Yazhou Ren, Lianyin Jia, Guoxian Yu. Drug Repositioning based on Individual Bi-random Walks on a Heterogenous Network. ISBRA, 2018, Accepted.
  5. Yazhou Ren, Peng Zhao, Yongpan Sheng, Dezhong Yao, and Zenglin Xu. Robust Softmax Regression for Multi-class Classification with Self-Paced Learning. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) (CCF A), 2017, pages 2641-2647.
  6. Yazhou Ren, Peng Zhao, Zenglin Xu, and Dezhong Yao. Balanced self-paced learning with feature corruption. In Proceedings of the International Joint Conference on Neural Networks (IJCNN) (CCF C), 2017, pages 2064-2071.
  7. Yazhou Ren, Uday Kamath, Carlotta Domeniconi, and Guoji Zhang. Boosted Mean Shift Clustering. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD) (CCF B), Nancy, France, September 15-19, 2014, pages 646–661.
  8. Yazhou Ren, Carlotta Domeniconi, Guoji Zhang, and Guoxian Yu. A Weighted Adaptive Mean Shift Clustering Algorithm. In Proceedings of the SIAM International Conference on Data Mining (SDM) (CCF B), Philadelphia, Pennsylvania, April 24 - 26, 2014, pages 794-802.
  9. Yazhou Ren, Carlotta Domeniconi, Guoji Zhang, and Guoxian Yu. Weighted-Object Ensemble Clustering. In Proceedings of the IEEE 13th International Conference on Data Mining (ICDM) (CCF B), Dallas, Texas, December 7 - 10, 2013, pages 627-636.
  10. Yanming Yu, Guo-Xian Yu, Xia Chen, and Yazhou Ren. Semi-supervised Multi-label Linear Discriminant Analysis. In Proceedings of International Conference on Neural Information Processing (ICONIP) (CCF C), 2017, pages 688-698.
  11. Xiaofan Que, Yazhou Ren, Jiayu Zhou, Zenglin Xu. Regularized Multi-source Matrix Factorization for Diagnosis of Alzheimer’s Disease. In Proceedings of International Conference on Neural Information Processing (ICONIP) (CCF C), 2017, pages 463-473.
  12. Bin Liu, Zenglin Xu, Bo Dai, Haoli Bai, Xianghong Fang, Yazhou Ren, Shandian Zhe. Learning from Semantically Dependent Multi-Tasks. In Proceedings of the 2017 International Joint Conference on Neural Networks (IJCNN) (CCF C), 2017, pages 3498-3505.
  13. Jiehua Wu, Guoji Zhang, Yazhou Ren, Xiayan Zhang and Guoxian Yu. Exploiting Neighbors’ Latent Correlation for Link Prediction in Complex Network. In Proceedings of 2013 International Conference on Machine Learning and Cybernetics (ICMLC) (EI), 2013, pages 1077-1082.

Journal papers

  1. Yazhou Ren, Kangrong Hu, Xinyi Dai, Lili Pan, Steven C.H. Hoi, Zenglin Xu. Semi-supervised Deep Embedded Clustering. Neurocomputing (SCI-II), 2019, 325: 121-130.
  2. Yazhou Ren, Carlotta Domeniconi, Guoji Zhang, and Guoxian Yu. Weighted-object ensemble clustering: methods and analysis. Knowledge and Information Systems (KAIS) (SCI-III,CCF B), 2017, 51(2):661-689.
  3. Yazhou Ren, Guoji Zhang, Guoxian Yu, and Xuan Li. Local and Global Structure Preserving based Feature Selection. Neurocomputing (SCI-II), 2012, 89:147-157.
  4. Yazhou Ren, Guoji Zhang, and Guoxian Yu. Random Subspace based Semi-Supervised Feature Selection. In Proceedings of 2011 International Conference on Machine Learning and Cybernetics (ICMLC) (EI), 2011, pages 113-118.
  5. Shudong Huang, Yazhou Ren, Zenglin Xu. Robust Multi-view Data Clustering with Multi-view Capped-Norm K-means. Neurocomputing (SCI-II), 2018, 311: 197–208.
  6. Jie Liu, Guoxian Yu, Yazhou Ren, Maozu Guo, Jun Wang. TrioMDR: Detecting SNP interactions in trio families with model-based multifactor dimensionality reduction. Genomics (SCI-III), 2018, https://doi.org/10.1016/j.ygeno.2018.07.014
  7. Weiwei Zhang, Bin Ye, Weijiang Liang, and Yazhou Ren (*). Preoperative prognostic nutritional index is a powerful predictor of prognosis in patients with stage III ovarian cancer. Scientific Reports (SCI-III), 2017, 7(1): 1-8.
  8. Weiwei Zhang, Kejun Liu, Weijiang Liang, Bin Ye, and Yazhou Ren (*). Pretreatment C‐reactive protein/albumin ratio is associated with poor survival in patients with stage IB‐IIA cervical cancer. Cancer Medicine (SCI-III), 2018, 7(1): 105-113.
  9. Guoxian Yu, Guangyuan Fu, Chang Lu, Yazhou Ren, and Jun Wang. BRWLDA: bi-random walks for predicting lncRNA-disease associations. Oncotarget (SCI-I), 2017, 8(36): 60429.
  10. Jun Wang, Long Zhang, Lianyin Jia, Yazhou Ren, Guo-Xian Yu. Protein-Protein Interactions Prediction Using a Novel Local Conjoint Triad Descriptor of Amino Acid Sequences. International Journal of Molecular Sciences (SCI-III), 2017, 18(11):1-17.
  11. Weiwei Zhang, Kejun Liu, Bin Ye, Yazhou Ren, and Weijiang Liang. Clinical and biological effects of tumor‑associated lymphocytes in the presence or absence of chemotherapy for malignant ascites in ovarian cancer patients. Oncology letters (SCI-IV), 2017, 14(3): 3379-3386.
  12. Jiehua Wu, Guoji Zhang, and Yazhou Ren. A balanced modularity maximization link prediction model in social networks. Information Processing and Management (IPM) (SCI-III), 2017, 53: 295–307.
  13. Jiehua Wu, Guoji Zhang, Yazhou Ren, Xiayan Zhang, and Qiao Yang. Weighted Local Naive Bayes Link Prediction, Journal of Information Processing Systems (EI), 2017, 13(4): 914-927.
  14. Xiayan Zhang, Guoji Zhang, Xuan Li, Yazhou Ren, and Jiehua Wu. Image encryption using random sequence generated from generalized information domain. Chinese Physics B (SCI-III), 2016, 25(5): 054201.
  15. 余国先,张国基,韦佳,任亚洲. 一种基于多图的集成直推分类方法. 电子与信息学报(EI), 2011, 33(8): 1883-1888.

International visiting and communication

08/2012~07/2014 Joint training of doctoral students of George Mason University, cooperative Mentor: Professor Carlotta Domeniconi.

Teaching courses

Artificial Intelligence,
Programming Foundation (C/C++),
Computer Vision

Research projects

  1. 01/2019~12/2021 Research of multi-task clustering based on self-paced learning(No. 61806043),NSFC,RMB 260,000,Principal Investigator.
  2. 01/2019~12/2023 New data management system(No. 61832001),NSFC,RMB 2,890,000, Participant.
  3. 01/2019~12/2022 Research and Application of Point Process in User Behavior Modeling(No. 61872062), NSFC, RMB 640,000, Participant。
  4. 01/2017 ~ 12/2018 Self-paced learning theory and its application in the diagnosis of Alzheimer’s disease (No. ZYGX2016J078), Fundamental Research Funds for the Central Universities of China, RMB 90,000, Principal Investigator.
  5. 01/2017 ~ 12/2017 Multi-Task Self-Paced Learning for Alzheimer’s Disease Diagnosis (No. 2016M602674), A project funded by China Postdoctoral Science Foundation, RMB 50,000, Principal Investigator.
  6. 01/2015 ~ 12/2016 Large-scale Nonparametric Clustering Analysis based on Ensemble Methods (No. ZYGX2015KYQD042), Fundamental Research Funds for the Central Universities of China, RMB 135,000, Principal Investigator.
  7. 01/2016 ~ 12/2019 Nonparametric Bayesian Learning for Large Scale Tensor Analysis (No. 61572111), National Natural Science Foundation, RMB 730,000, Participant.
  8. 01/2016 ~ 12/2016 Content-based intelligent recommendation scene and algorithm based on big data of mobile Internet (No. MCM20150505), Joint Foundation of the Ministry of Education of China and China Mobile Communication Corporation, RMB 1 million, Participant.
  9. 01/2015 ~ 12/2016 Extensible Bayesian learning algorithm and its application in large-scale social networks (No. CASNDST201402), Open Fund from CAS Key Lab of Network Data Science and Technology, Institute of Computing Technology, Chinese Academy of Sciences, RMB 60,000, Participant.

Contact information

E-mail: yazhou.ren@uestc.edu.cn

Address:No.2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, Sichuan, P.R.China