General

Qing He, Male, Chinese, Professor, Ph. D. Supervisor,
The Key Laboratory of Intelligent Information Processing,
Institute of Computting Technology,
Chinese Academay of Sciences,
Beijing,China
100190
Email: heqing@ict.ac.cn
Telephone: 8610-62600542
Address: Kexueyuan Nan Road No.6, Haidian District, Beijing,China
Webpage: http://mldm.ict.ac.cn/

Research Areas

Machine Learning; Data Mining Based Cloud Computing; Web Mining;  Artificial Intelligence

Education

Date
Degree
University
Mayjor
1981.9-1985.7
Bachelor
Hebei Normal University
Mathematics
1985.8-1987.7
Master
Zhengzhou University
Mathematics
1997.8-2000.7
Ph. D.
Beijing Normal University
Fuzzy Mathematics and Artificial Intelligent
2000.8-2002.8
Post Ph. D.
Institute of Computing and Technology, CAS
Computer Software and Theory

St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, Visiting Professor , 2001.11
University of Technology, SydneyUniversity of Technology, Sydney, Visiting Professor, 2003.10

Experience

   
Work Experience

Qing He is a Professor at the Institute of Computing Technology, Chinese Academy of Sciences(CAS), and he is a Professor of University of Chinese Academy of Sciences (UCAS). He is also the Vice Secretary of Chinese Association for Artificial Intelligence,
the Member of China Computer Federation Artificial Intelligence and Pattern Recognition Committee, the Member of Chinese Insititue of Electronics and Clouding Computing  and Big Data Experts Committee. He received the B.S. degree from Hebei Normal University, Shijiazhuang, P. R. C., in 1985, and the M.S. degree from Zhengzhou University, Zhengzhou, P. R. C., in 1987, both in Mathematics. He received the Ph.D. degree in 2000 from Beijing Normal University in Fuzzy Mathematics and Artificial and Intelligence, Beijing, P. R. C. Since 1987 to 1997, he had been teaching at Hebei University of Science and Technology. He is currently a doctoral supervisor at the Institute of Computing and Technology, CAS. His interests include data mining, machine learning, classification, fuzzy clustering,cloud computing,big data. A series of achievements have been gained in fuzzy information processing, fuzzy clustering, knowledge representation, text information processing, and in big data mining based on cluoud computing. More than 100 papers have been published in journals, 40 of which are SCI Indexed, 66 of which are EI Indexed. Multi-strategy data mining platform MSMiner, Web Intelligent Information Processing software GHunt, Hypersurface Classifier HSC, have been organized and developed. Recently, in cloud computing and big data mining applications, Qing He led his machine learning and data mining team (http://mldm.ict.ac.cn/Home.html), commissioned by the China Mobile Research Institute, developed cloud-based parallel data mining platform by the end of 2008 for mining TB level actual data and achieving high-performance, low-cost data mining. Through this innovation, the country received a proprietary cloud-based data mining techniques. Assembly invited he made a technical report in the second, third, sixth China Cloud Computing Conference. He has presided and completed a number of relevant data mining project supported by the National Natural Science Foundation and 863 projects. Moreover, the projects were rated excellent. He proposed a series of effective data mining algorithms and multiple parallel machine learning algorithms. He organized his team developing forty parallel machine learning algorithms. Multiple big data mining software such as PDMiner,COMS,CWMS and WMCS developed by his team have gotten the software copyright and practical applying to telecommunications, electricity, information security, environmental protection, the financial insurance, and dozens of companies, enterprises with the considerable economic and social benefits.



Teaching Experience

Professor of  Graduate of Chinese Academey of Sciences

Course: Fuzzy Mathematics and Application in Computing

Honors & Distinctions

2015 Wenjun Wu Artificial Intelligence Innovation Award

2006 Beijing Science Technology Award


Publications

   
Papers



一、会议论文

[1]      Dongbo Xi, Fuzhen Zhuang, Bowen Song, Yongchun Zhu, Shuai Chen, Dan Hong, Tao Chen, Xi Gu, Qing He. Neural Hierarchical Factorization Machines for User's Event Sequence Analysis. SIGIR20 short paper, July 25-30, 2020, Xi'an, China. 

[2]      Dongbo Xi, Fuzhen ZhuangGanbin ZhouXiaohu ChengFen LinQing He. Domain Adaptation with Category Attention Network for Deep Sentiment Analysis. WWW’20, April 2024, 2020, Taipeipp.: 3133-3139.

[3]      Feiyang Pan, Xiang Ao, Pingzhong Tang, Min Lu, Dapeng Liu, Lei Xiao and Qing He. Field-aware calibration: a simple and empirically strong method for reliable probabilistic predictions. WWW’20, April 2024, 2020, Taipei

[4]      Qiwei ZhongYang LiuXiang AoBinbin HuJinghua FengJiayu TangQing He. Financial Defaulter Detection on Online Credit Payment via Multi-view Attributed Heterogeneous Information NetworkWWW’20, April 2024, 2020, Taipei

[5]      Yongchun Zhu, Dongbo Xi, Bowen Song, Fuzhen Zhuang, Shuai Chen, Gu Xi, and Qing He. Modeling Users’ Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection. Proceedings of the Web Conference 2020. pp.: 928-938. WWW’20, April 2024, 2020, Taipei

[6]      Zhao Zhang, Fuzhen Zhuang*, Hengshu Zhu, Zhiping Shi, Hui Xiong, Qing He, Relational Graph Neural Network with Hierarchical Attention for Knowledge Graph Completion. AAAI 2020, Feb.7-12,Newyork USA.

[7]    Dongbo Xi, Fuzhen Zhuang, Yanchi Liu, Jingjing Gu, Hui Xiong, Qing He. Modeling Users’ Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection[C]// WWW’20, April 2024, 2020, Taipei

[8]      Dongbo Xi, Fuzhen Zhuang*, Yanchi Liu, Jingjing Gu, Hui Xiong, Qing He: Modelling of Bi-directional Spatio-Temporal Dependence and Users' Dynamic Preferences for Missing POI Check-in Identification. AAAI 2019.

[9]      Feiyang Pan, Qingpeng Cai, An-Xiang Zeng, Chun-Xiang Pan, Qing Da, Hualin He, Qing He, Pingzhong Tang. Policy Optimization with Model-based Explorations. AAAI 2019.

[10]   Feiyang Pan, Shuokai Li, Xiang Ao, Pingzhong Tang, Qing He. Warm Up Cold-start Advertisements : Improving  CTR Predictions via Learning to Learn ID Embeddings. To appear in the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019). 

[11]   Pan feiyang, Cai, Qi,Tang, Pingzhong, Zhuang, Fuzhen., He, Qing. Policy gradients for contextual recommendations,WWW2019

[12]   Ying Sun, Fuzhen Zhuang, Hengshu Zhu, Xin Song, Qing He, Hui Xiong. A Structure-Aware Convolutional Neural Network Approach, KDD2019

[13]   Ling Luo, Xiang Ao,Yan Song,Jinyao Li,Xiaopeng Yang,Qing He,Dong Yu, Unsupervised Neural Aspect Extraction with Sememes,IJCAI2019

[14]   Ying Sun, Hengshu Zhu, Fuzhen Zhuang, Jingjing Gu and Qing He Exploring the Urban Region-of-Interest through the Analysis of Online Map Search QueriesKDD2018

[15]   Ganbin Zhou, Ping Luo, Rongyu Cao, Yijun Xiao, Fen Lin, Bo Chen, Qing He. Tree-Structured Neural Machine for Linguistics-Aware Sentence GenerationThe Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18) February 2–7, 2018New Orleans, Lousiana, USA

[16]   Ganbin Zhou, Ping Luo, Yijun Xiao, Fen Lin, Bo Chen, Qing He. Elastic Responding Machine for Dialog Generation with Mechanism Dynamically SelectingThe Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18) February 2–7, 2018New Orleans, Lousiana, USA

[17]   Jingwu Chen, Fuzhen Zhuang, Xin Hong, Xiang Ao, Xing Xie and Qing He: Attention-driven Factor Model for Explainable Personalized Recommendation. SIGIR 2018

[18]   Xiang Ao, Yang Liu, Zhen Huang, Luo Zuo, Qing He. Free-rider Episode Screening via Dual Partition Model. The 23rd International Conference on Database Systems for Advanced Applications (DASFAA), 2018.

[19]   Ling Luo, Xiang Ao, Feiyang Pan, Tong Zhao, Ningzi Yu, Qing He. Beyond Polarity: Interpretable Financial Sentiment Analysis with Hierarchical Query-driven Attention. The 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018.

[20]   Jia He, Changying Du, Changde Du, Fuzhen Zhuang, Qing He, Guoping Long.Nonlinear Maximum Margin Multi-view Learning with Adaptive Kernel,IJCAI17

[21]   Ganbin Zhou, Ping Luo, Rongyu Cao, Fen Lin, Bo Chen, Qing He. Mechanism-Aware Neural Machine for Dialogue Response GenerationAAAI2017

[22]   Xiang Ao, Ping Luo, Jin Wang, Fuzhen Zhuang, Qing He. Mining Precise-positioning Episode Rules from Event SequencesICDE2017

[23]   Fuzhen Zhuang, Jing Zheng, Chuan Shi and Qing He.Transfer Collaborative Filtering from Multiple Sources via Consensus Regularization,WSDM2017

[24]   Qing He, Yunlong Ma, Qun Wang, Fuzheng Zhuang, Zhongzhi Shi. Parallel Outlier Detection Using KD-Tree Based on MapReduce, IEEE CloudCom 2011,Washington, DC, USA, 4-9 July, 2011

[25]   Qing He, Zhongzhi Shi, Lian Ren.The Classification Method Based on Hyper Surface2002 International Joint Conference on Neural Networks2002.5:1499-1503, Honolulu, Hawaii,USA, May 12-17, 2002

[26]   Qing He, Xiurong Zhao, Sulan Zhang. Multi-modal services for web information collection based on multi-agent techniques, Lecture Notes in Computer Science, v 4088 LNAI, Agent Computing and Multi-Agent Systems: 9th Pacific Rim International Workshop on Multi-Agents, PRIMA 2006, p 129-137, Guilin, China, in August 2006

[27]   Jia He, Changying Du, Fuzhen Zhuang,Yin Xin, Qing He*, Guoping Long. Online Bayesian Max-margin Subspace Multi-view Learning, IJCAI-16July 9–15, 2016, New York

[28]   Ping Luo, Ganbin Zhou, Qing He*. Browsing Regularities in Hedonic Content Systems: the More the Merrier? IJCAI-16July 9–15, 2016, New York

[29]   Xiang Ao, Ping Luo, Chengkai Li, Fuzhen Zhuang, Qing He*. Online Frequent Episode Mining, ICDE 2015 : International Conference on Data Engineering (ICDE15), Seoul, Korea, April 13-17, 2015

[30]   Changying Du, Shandian Zhe, Fuzhen Zhuang, Alan Qi, Qing He*, Zhongzhi Shi. Bayesian Maximum Margin Principal Component Analysis, Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15)Austin, Texas, USA, January 25–30, 2015,

[31]   Xinyu Wu, Ping Luo, Qing He*, Tianshu Feng. Festival, Date and Limit Line: Predicting Vehicle Accident Rate in Beijing, SDM15, British Columbia, Canada, April 30-May 2

[32]   Xiang Ao, Ping Luo, Chengkai Li, Fuzhen Zhuang, Qing He*, Zhongzhi Shi.Discovering and learning sensational episodes of news events. The 23rd international conference on World Wide Web, WWW2014, Seoul, Korea, April 7-11,

[33]   Wenjuan Luo, Fuzhen Zhuang, Xiaohu Cheng, Qing He*, Zhongzhi Shi. Ratable Aspects over Sentiments: Predicting Ratings for Unrated Reviews, IEEE International Conference on Data Mining (ICDM 2014), Shenzhen, China,December 14-17, 2014

[34]   Xin Jin, Fuzhen Zhuang, Hui Xiong, Changying Du, Ping Luo and Qing He*. Multi-task Multi-view Learning for Heterogeneous Tasks, CIKM’14, November 03–07, 2014, Shanghai, China

[35]   Fuzhen Zhuang, Xiaohu Cheng, Sinno Jialin Pan, Wenchao Yu, Qing He*, Zhongzhi Shi. Transfer Learning with Multiple Sources via Consensus Regularized Autoencoders, The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML14/PKDD14), Nancy, France, September 15th to 19th, 2014.

[36]   Changying Du, Jia He, Fuzhen Zhuang, Yuan Qi, Qing He*. Nonparametric Bayesian Multi-Task Large-margin Classification, 21st European Conference on Artificial intelligence (ECAI14), Prague, Czech, 18-22 Aug. 2014.

[37]   Shuo Han, Fuzhen Zhuang, Qing He*, Zhongzhi Shi. Balanced Seed Selection for Budgeted Influence Maximization in Social Networks, PAKDD 2014: Pacific-Asia Conference on Knowledge Discovery and Data Mining , 2014-05-13, Tainan, Taiwan, China

[38]   Xiang Ao, Ping Luo, Chengkai Li, Fuzhen Zhuang, Qing He*, Zhongzhi Shi. Discovering and learning sensational episodes of news events. The 23rd international conference on World Wide Web, WWW2014, Seoul, Korea,April 7-11

[39]   Wenjuan Luo, Fuzhen Zhuang, Xiaohu Cheng, Qing He*, Zhongzhi Shi. Ratable Aspects over Sentiments: Predicting Ratings for Unrated Reviews, IEEE International Conference on Data Mining (ICDM 2014), Shenzhen, China / December 14-17, 2014

[40]   Xin Jin, Fuzhen Zhuang, Hui Xiong, Changying Du, Ping Luo and Qing He*. Multi-task Multi-view Learning for Heterogeneous Tasks, CIKM’14, Shanghai, China, November 03–07, 2014

[41]   Shuo Han, Fuzhen Zhuang, Qing He*, Zhongzhi Shi. Balanced Seed Selection for Budgeted Influence Maximization in Social Networks, PAKDD 2014 : Pacific-Asia Conference on Knowledge Discovery and Data Mining, Tainan, Taiwan, China,2014-05-13

[42]   Fuzhen Zhuang, Ping Luo, Changying Du, Qing He*, Zhongzhi Shi. Triplex Transfer Learning: Exploiting both Shared and Distinct Concepts for Text Classification, WSDM’13, Rome, Italy, February 4–8, 2013

[43]   Fuzhen Zhuang, Ping Luo, Peifeng Yin, Qing He*, Zhongzhi Shi. Concept Learning for Cross-domain Text Classification: a General Probabilistic Framework, 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013). Beijing, China, August 3-9, 2013

[44]   Tianfeng Shang, Qing He*, Fuzhen Zhuang and Zhongzhi Shi. A New Similarity Measure Based on Preference Sequence for Collaborative Filtering. Web Technologies and Applications. 15th Asia-Pacific Web Conference, APWeb 2013,Sydney, NSW, Australia, 4-6 April 2013

[45]   Tianfeng Shang, Qing He*, Fuzhen Zhuang, Zhongzhi Shi. Extreme Learning Machine Combining Matrix Factorization for Collaborative Filtering. IEEE The 2013 International Joint Conference on Neural Networks, IJCNN 2013, Dallas, TX, USA, August 4-9, 2013.

[46]   Xin Jin, Fuzhen Zhuang, Shuhui Wang, Qing He*, and Zhongzhi Shi. Shared Structure Learning for Multiple Tasks with Multiple Views, ECML/PKDD13, Prague, September 23-27, 2013

[47]   Wenchao Yu, Guangxiang Zeng, Ping Luo, Fuzhen Zhuang,Qing He*, and Zhongzhi Shi. Embedding with Autoencoder Regularization, ECML/PKDD13, Prague,September 23-27, 2013

[48]   Changying Du, Fuzhen Zhuang, Qing He* and Zhongzhi Shi. Multi-Task Semi-Supervised Semantic Feature Learning for Classification, ICDM2012pp. 191-200, Brussels, Belgium, 2012 (12/10-12/13)

[49]   Wenjuan Luo Fuzhen Zhuang, Qing He*, and Zhongzhi Shi. Quad-tuple PLSA: Incorporating Entity and Its Rating in Aspect Identification, The 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), PAKDD 2012, pp. 392–404, Kuala Lumpur, Malaysia, 29 May - 1 June,2012

[50]   Xudong Ma, Ping Luo, FuzhenZhuang, Qing He*, Zhongzhi Shi and ZhiyongShen. Combining Supervised and Unsupervised Models via Unconstrained Probabilistic Embedding, Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI 11pp.1396-1401C,Barcelona in July 2011

[51]   Fuzhen Zhuang, Ping Luo, Hui Xiong, Qing He*. Yuhong Xiong. Exploiting Associations between Word Clusters and Document Classes for Cross-domain Text Categorization, 2010 SIAM International Conference on Data Mining (SDM'2010), pp.13-24, Columbus, Ohio, April 19, 2010(EI,被大会推荐的十二篇最佳论文提名之一)

[52]   Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He*, Yuhong Xiong, and Zhongzhi Shi. D-LDA: A Topic Modeling Approach without Constraint Generation for Semi-Defined Classification, accepted as a regular paper at the IEEE International Conference on Data Mining (ICDM 2010) to be held in Sydney Australia, December 14-172010, pp.709-718, (EI )

[53]   Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He*, Yuhong Xiong, Zhongzhi Shi1, Hui Xiong. Collaborative Dual-PLSA: Mining Distinction and Commonality across Multiple Domains for Classification, The 19th ACM International Conference on Information and Knowledge Management( CIKM’10), October 26-30, 2010, Toronto, Canada. (获得八篇最佳论文提名之一并获得Student Travel Awards)

[54]   Qing Tan, Qing He*, Zhongzhi Shi. Nonparametric Curve Extraction Based on Ant Colony System, Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10), pp.599-604, Atlanta, USA, July 10-15, 2010

[55]   Weizhong Zhao, Huifang Ma, Qing He.Parallel k-means clustering based on mapreduce, Cloud Computing, 2009

[56]   Ping Luo, Fuzhen Zhuang, Hui Xiong, Yuhong Xiong, Qing He*. Transfer Learning from Multiple Source Domains via Consensus Regularization, full paper in CIKM 2008 ,  Napa Valley, California October 26-30, 2008 (EI)

[57]   Qiuge Liu, Qing He*, Zhongzhi Shi. Extreme Support Vector Machine Classify, Lecture Notes in Computer Science, v 5012 LNAI, Advances in Knowledge Discovery and Data Mining, 12th Pacific-Asia Conference, PAKDD 2008, Proceedings, 2008, p 222-233,Osaka,Japan,May 20-23,2008(EI)

[58]   Luo, Ping; Lu, Kevin; He, Qing*; Shi, Zhongzhi. A heterogeneous computing system for data mining workflows, Lecture Notes in Computer Science, v 4042 LNCS, Flexible and Efficient Information Handling - 23rd British National Conference on Databases, BNCOD 23, Proceedings, 2006, p 177-189, Belfast, Northern Ireland, UK, July 18-20, 2006

[59]   Zheng, Zheng; He, Qing*; Shi, Zhongzhi. Granule sets based bilevel decision model, Lecture Notes in Computer Science, v 4062, Rough Sets and Knowledge Technology - First International Conference, RSKT 2006, Proceedings, 2006, p 530-537, Chongqing, China, July 24-26, 2006 

[60]   Zhao, Xiu-Rong; He, Qing*; Shi, Zhong-Zhi. HyperSurface Classifiers ensemble for high dimensional data sets, Lecture Notes in Computer Science, v 3971, Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, p 1299-1304, Chengdu, China, May 28 - June 1, 2006

[61]   Ping Luo, Qing He*, Rui Huang, Fen Lin, Zhongzhi Shi. Execution Engine of Meta-learning System for KDD in Multi-agent Environment. Lecture Notes in Computer Science. Springer-Verlag, Volume 3505 / 2005, 149-160. AIS-ADM 2005, St. Petersburg, Russia, June 6-8, 2005

[62]   Ping Luo, Su Yan, Zhiqiang Liu, Zhiyong Shen, Shengwen Yang, Qing He. From Online Behaviors to Offline Retailing, the ACM KDD 2016 Conference as a full presentationCCF A

 

二、期刊论文

[1]      Fuzhen Zhuang, Yingmin Zhou, Haochao Ying, Fuzheng Zhang, Xiang Ao, Xing Xie, Qing He, Hui Xiong: Sequential Recommendation via Cross-domain Novelty Seeking Trait Mining. Accepted by Journal of Computer Science and Technology, 2020.

[2]      Jia HeOnline Bayesian Max-margin Subspace Learning for Multi-view Classification and Regression, Accepted by Machine Learning.

[3]      Jingwu Chen, Fuzhen Zhuang, Tianxin Wang, Leyu Lin, Feng Xia, Lihuan Du, Qing He. Follow the Title then Read the Article: Click-guide Network for Dwell Time Prediction, Accepted by IEEE Transactions on Knowledge and Data Engineering

[4]      Yang Liu, Xiang Ao, Linfeng Dong, Chao Zhang, Jin Wang, Qing He. Spatiotemporal Activity Modeling via Hierarchical Cross-Modal Embedding. Accepted by IEEE Transactions on Knowledge and Data Engineering. 2020.

[5]      Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, Qing He: Deep Subdomain Adaptation Network for Image Classification. IEEE Transactions on Neural Networks and Learning Systems.

[6]      Zhao Zhang, Fuzhen Zhuang, Xuebing Li, Zhengyu Niu, Jia He, Qing He, Hui Xiong: Knowledge Triple Mining via Multi-Task Learning. Information Systems, Information Systems 80 (2019) 64–75

[7]      Xiang Ao, Haoran Shi, Jin Wang, Luo Zuo, Hongwei Li, Qing He. Large-scale Frequent Episode Mining from Complex Event Sequences with Hierarchies. ACM Transactions on Intelligent Systems and Technology (ACM TIST). 

[8]      Thapana Boonchooa, Xiang Ao, Yang Liu, Weizhong Zhao, Fuzhen Zhuang, Qing He. Grid-based DBSCAN : Indexing and Inference. Pattern Recognition (PR), 90 : 271-284, 2019

[9]      Zhou Ganbin Luo Ping He Qing. Predicting Compositional Time Series via Autoregressive Dirichlet Estimation, SCIENCE CHINA Information Sciences (accepted)

[10]   Xiang Ao, Ping Luo, Jin Wang, Fuzhen Zhuang and Qing He. Mining Precise-positioning Episode Rules from Event Sequences, acceped by IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

[11]   Fuzhen Zhuang, Xuebing Li, Xin Jin, Dapeng Zhang, Lirong Qiu, Qing He: Semantic Feature Learning for Heterogeneous Multi-task Classification via Non-negative Matrix Factorization. IEEE Transactions on Cybernetics, 2017.

[12]   Xuebing Li, Ying Sun, Fuzhen Zhuang, Jia He, Zhao Zhang, Shijun Zhu, Qing He: Potential Off-grid User Prediction System Based on Spark. ZTE Communications, 2018. (Accepted)

[13]   Qing He, Haocheng Wang, Fuzhen Zhuang, Tianfeng Shang, Zhongzhi Shi. Parallel sampling from big data with uncertainty distribution, Fuzzy Sets and Systems 258 (2015) 117–133 (SCI)

[14]   Qing He, Xin Jin, Changying Du, Fuzhen Zhuang and Zhongzhi Shi. Clustering in extreme learning machine feature space. Neurocomputing 128 : 88-95 (2014). (SCI).

[15]    Qing He, Tianfeng Shang, Fuzhen Zhuang and Zhongzhi Shi. Parallel Extreme Learning Machine for Regression based on MapReduce, Neurocomputing 102(2013)52–58 (SCI\EI)

[16]    He, Qing; Zhao, Weizhong; Shi, Zhongzhi. CHSMST: A clustering algorithm based on hyper surface and minimum spanning tree, Soft Computing, v 15, n 6, p 1097-1103, June 2011(SCI\EI)

[17]   Qing He, Changying Du, Qun Wang, FuzhenZhuang, Zhongzhi Shi. A Parallel Incremental Extreme SVM Classifier, Neurocomputing74 (2011) 2532–2540 (SCI\EI )

[18]   Qing He, Xiurong Zhao, Zhongzhi Shi.Minimal consistent subset for Hyper Surface Classification method. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE Volume: 22 Issue: 1 Pages: 95-108, FEB 2008.(SCI\EI)

[19]   Qing He, Xiurong Zhao, Zhongzhi Shi. Classification based on dimension transposition for high dimension dataInternational Journal Soft Computing 11(4),2007, pp: 329 - 334(SCI)

[20]   Qing He, Zhongzhi Shi,Li-an Ren, E.S. Lee. A Novel Classification Based on Hypersurface. International Journal of Mathematical and Computer Modeling 38(2003),395-407 (SCI)

[21]   Qing He, Hongxing Li, Zhongzhi Shi, E.S.Lee. On Fuzzy Clustering Method Based on Perturbation. Computers and Mathematics with Applications, v 46, n 5-6, September, 2003, p 929-946 (SCI\EI)

[22]    Qing He, Hongxing Li, C.L.P. Chen, E.S. Lee. Extension Principles and Fuzzy Set Categories. International Journal of Computers and Mathematics with Applications 2000, 39: 45-53(SCI)

[23]   Jie Lu, Zheng Zheng, Guangquan Zhang, Qing He* and Zhongzhi Shi. A new solution algorithm for solving rule-sets based bilevel decision problems, CONCURRENCY AND COMPUTATION: PRACTICE AND EXPERIENCE. Vol: 27, No: 4,pages: 830-54 (SCI\EI)

[24]   Wenjuan Luo, Fuzhen Zhuang, Weizhong Zhao, Qing He*, Zhongzhi Shi. QPLSA: Utilizing quad-tuples for aspect identification and rating, Information Processing and Management 51 (2015) 25–41(SCI\EI)

[25]   Wenchao Yu, Fuzhen Zhuang, Qing He* and Zhongzhi Shi. Learning Deep Representations via Extreme Learning Machine, Neurocomputing, Volume 149, Part A, 3 February 2015, Pages 308-315 (SCI\EI)

[26]   Xiang Ao; Ping Luo; Xudong Ma; Fuzhen Zhuang; Qing He*; Zhongzhi Shi; Zhiyong Shen. Combining Supervised and Unsupervised Models via Unconstrained Probabilistic Embedding, Information Sciences, 257 (2014) 101–114. (SCI impact factor (2012): 3.643)

[27]   Fuzhen Zhuang, Ping Luo, Changying Du, Qing He*, Zhongzhi Shi, Hui Xiong: Triplex transfer learning: exploiting both shared and distinct concepts for text classification, IEEE TRANSACTIONS ON CYBERNETICS, VOL. 44, NO. 7, 1191-1203, JULY 2014 (impact factor (2012): 3.236) (SCI\EI)

[28]   Shuo Han, Fuzhen Zhuang, Qing He*, Zhongzhi Shi, & Xiang Ao. Energy model for rumor propagation on social networks. Physica A: Statistical Mechanics and its Applications394 (2014) 99–109 (SCI impact factor (2012): 1.676).

[29]   Shuo HanQing He*Zhongzhi Shi. Energy Model for Rumor Propagation on Social Networks. Physica A: Statistical Mechanics and its Applications394 (2014) 99–109.

[30]   Wenjuan Luo, Fuzhen Zhuang, Qing He*, Zhongzhi Shi Exploiting relevance, coverage, and novelty for query-focused multi-document summarizationKnowledge-Based Systems. Volume 46, July 2013, Pages 33–42 . (SCI\EI)

[31]   Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He*, Yuhong Xiong, Zhongzhi Shi and Hui Xiong. Mining Distinction and Commonality across Multiple Domains using Generative Model for Text Classification, IEEE Transactions on Knowledge and Data Engineering, VOL. 24, NO. 11, NOVEMBER 2012,2025-2039(SCI\EI )

[32]   Zhiping Shi, Xi Liu, Qingyong Li, Qing He*, Zhongzhi Shi, Extracting Discriminative Features for CBIR, MULTIMEDIA TOOLS AND APPLICATIONS Volume 61, Number 2 (2012), 263-279(SCI)

[33]   Fuzhen Zhuang, George Karypis, Xia Ning, Qing He*, Zhongzhi Shi. Multi-view learning via probabilistic latent semantic analysis, Information Sciences,199 (2012) 20–30(SCI\EI)

[34]   Weizhong Zhao, Qing He*, Huifang Ma, Zhongzhi Shi. Effective Semi-supervised Document Clustering via Active Learning with Instance-level Constraints, Knowledge and Information Systems (2012) 30:569–587 (SCI\EI)

[35]   Tan, Qing; He, Qing*; Zhao, Weizhong; Shi, Zhongzhi; Lee, E.S. An improved FCMBP fuzzy clustering method based on evolutionary programming, Computers and Mathematics with Applications, v 61, n 4, p 1129-1144, February 2011(SCI\EI)

[36]   Guang-Quan Zhang, ZhengZheng, Jie Lu, Qing He*. An Algorithm for Solving Rule-Sets Based Bilevel Decision Problems, COMPUTATIONAL INTELLIGENCE Vol.27 No.2 pp.235-259, 2011 (SCI\EI)

[37]   Fuzhen Zhuang, Ping Luo, Hui Xiong, Yuhong Xiong, Qing He*, and Zhongzhi Shi. Cross-Domain Learning from Multiple Sources: A Consensus Regularization Perspective, IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, December 2010 (vol. 22 no. 12) ,pp. 1664-1678 (SCI\EI)

[38]   Zheng, Z., Lu, J, Zhang G, He Q*, Rule sets based bilevel decision model and algorithm, Expert Systems with Applications, 2009. Vol. 36, No. 1, 18-26(SCI)

[39]   Shifei Ding, Yongping Zhang, Xiaofeng Lei, Xinzheng Xu, Xin Wang, Li Wang, Qing He*. Research on a principal components decision algorithm based on information entropy, Journal of Information Science, Vol. 35, No. 1, 120-127 (2009) (SCI)

[40]   Zhuang F Z, Luo P, He Q, et al. Inductive transfer learning for unlabeled target-domain via hybrid regularization. Chinese Sci Bull, 2009, 54: 2470―2478 (SCI)

[41]   Zhiping Shi, Qing He*, Zhongzhi Shi. An Index and Retrieval Framework Integrating Perceptive Features and Semantics for Multimedia Database. Multimedia Tools and Application (2009) 42:207–231 Springer (SCI)

[42]   Zheng, Z., Lu, J, Zhang G, He Q*, Rule sets based bilevel decision model and algorithm, Expert Systems with Applications, 2009. Vol. 36, No. 1, 18-26(SCI)

[43]   Ping Luo, Guoxing Zhan, Qing He*, Zhongzhi Shi, and Kevin Lu, On Defining Partition Entropy by Inequalities. IEEE TRANSACTIONS ON INFORMATION THEORY, v53, n 9, SEPTEMBER 2007, p 3233-3239.SCI

[44]   Ping Luo; Lu, Kevin; Shi, Zhongzhi; He, Qing*. Distributed data mining in grid computing environments. Future Generation Computer Systems, v 23, n 1, Jan 1, 2007, p 84-91(SCI\EI)

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Copyright of Softwares

WMCS、CWMS、COMS、PDMiner、HSC

Collaboration

Rutgers, the State University of New Jersey
St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences
University of Technology, SydneyUniversity of Technology, Sydney