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姓名:余国先性别:
学历:博士 职称:教授
部门:电子商务系电话:023-68254396
邮件地址:gxyu@swu.edu.cn; guoxian85@gmail.com
研究方向:机器学习,数据挖掘,生物信息学。
个人简介

教授,博(硕)士生导师,重庆市学术技术带头人后备人。泄扑慊Щ峄嵩保ㄈ斯ぶ悄苡肽J绞侗鹱ㄎ嵛、生物信息学专业组委员、大数据专委会通讯委员),中国人工智能学会会员(生物信息学与人工生命专委会委员、机器学习专委会委员),IEEE/ACM会员,中国生物工程学会会员。普京游戏大厅机器学习与数据分析实验室负责人(团队主页http://mlda.swu.edu.cn/,个人相关主页:Google Scholar, DBLP

 

工作(教育)经历

2018- 普京游戏网站 教授 博/硕士生导师

2013-2018 普京游戏网站 副教授 硕士生导师

2014-2015年 香港浸会大学 计算机科学系 博士后研究员

2011-2013年 美国乔治梅森大学(George Mason University) 国家公派联合培养博士生

2007-2013年 华南理工大学 计算机科学与工程学院 计算机应用技术工学博士

2003-2007年 西安理工大学 计算机科学与工程学院 软件工程学士

 


研究兴趣:机器学习,数据挖掘与生物信息学,包括但不限于多标记学习,多视图学习,多示例学习,集成学习,多源数据整合,大数据分析,深度学习与大规模并行数据分析,基于机器学习和数据挖掘技术的分子功能预测和疾病关联分析等。

 

近年来,在国际顶级会议(SIGKDD, IJCAI, AAAI, ICDM, SDM等), 国内外知名期刊(TKDE, IEEE Trans on Cybernetics, IEEE Trans. on Big Data, Bioinformatics,Briefings in Bioinformatics, TCBB, 中国科学-信息科学,计算机学报,软件学报等)发表论文100余篇。

 

作为负责人主持(完成)国家自然科学基金3项(61872300, 61741217, 61402378)、重庆市自然科学基金2项(cstc2018jcyjAX0228, cstc2014jcyjA40031)、教育部中央高校重点项目2项,一般项目1项,重庆市研究生教改项目1项。

受邀担任KDD16-19, NeurIPS19, IJCAI19-20, AAAI19-20, ICDM14-20, SDM14-20, ISBRA16-20, BIBM等国际国内会议程序委员会委员(Program Committee), IEEE/ACM Trans. on XXX, Information Fusion, Pattern Recognition, Neurocomputing,自动化学报,计算机学报,中国科学-信息科学等多个国内外著名期刊审稿人。

教学情况
本科生:数据库原理导论;数据库综合课程设计;Matlab程序设计与实践;Java语言
研究生: 机器学习;数据挖掘;模式识别
普京游戏大厅含弘学院专业导师
论文(部分)情况


国内期刊论文(+指导的学生,*通讯作者):

[1].赵颖闻+,王峻,郭茂祖,张自力,余国先*.基于0-1矩阵分解的蛋白质功能预测, 中国科学-信息科学, 2019, 49(9): 1159-1174.

[2]. 路畅+,陈霞,王峻,余国先*,余志文. 基于稀疏语义的蛋白质噪声功能标注识别, 中国科学-信息科学, 2018. 48(8): 1035-1050.

[3]. 余国先*,傅广垣+,王峻,郭茂祖. 基于降维的蛋白质不相关功能预测, 中国科学-信息科学, 2017, 47(10): 1349-1368.

[4]. 傅广垣+,余国先*,王峻,张自力. 基于有向混合图的蛋白质新功能预测, 中国科学-信息科学, 2016, 46(4): 461-475.

[5].王星+,王峻*,余国先,郭茂祖. 基于网络约束双聚类的癌症亚型分类, 计算机学报, 2019, 42(6): 1274-1288. 

[6]. 谭桥宇+,余国先,王峻*,郭茂祖. 基于标记与特征依赖最大化的弱标记集成分类, 软件学报, 2017,28(11): 2851-2864.

[7]. 余国先,王可尧,傅广垣,王峻*,曾安. 基于多网络数据协同矩阵分解的蛋白质功能预测, 计算机研究与发展, 2017, 54(12): 2660-2673.

[8]. 傅广垣+,余国先*,王峻,郭茂祖. 基于正负样例的蛋白质功能预测, 计算机研究与发展, 2016, 53(8): 1753-1765.


 

国际会议论文

[1]. Jinzheng Tu+, Guoxian Yu*, Jun Wang, Carlotta Domeniconi, Xiangliang Zhang. Attention-Aware Answers of the Crowd, 20th SIAM Conference on Data Mining (SDM) (CCF Rank B), In Print, 2020.

[2]. Shaowei Wei+, Jun Wang*, Guoxian Yu, Carlotta Domeniconi, Xiangliang Zhang. Multi-View Multiple Clusterings using Deep Matrix Factorization, 34rd AAAI Conference on Artificial Intelligence (AAAI) (CCF Rank A), In Print, 2020.

[3]. Shixin Yao+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Xiangliang Zhang Multi-View Multiple Clustering, 28th International Joint Conference on Artificial Intelligence (IJCAI) (CCF Rank A), 2019, pp. 4121-4127.

[4]. Xia Chen+, Guoxian Yu*, Jun Wang, Carlotta Domeniconi, Zhao Li, Xiangliang Zhang. ActiveHNE: Active Heterogeneous Network Embedding, 28th International Joint Conference on Artificial Intelligence (IJCAI) (CCF Rank A), 2019, pp. 2123-2129.

[5]. Xing Wang+, Jun Wang*, Carlotta Domeniconix, Guoxian Yu, Guoqiang Xiao, Maozu Guo Multiple Independent Subspace Clusterings, 33rd AAAI Conference on Artificial Intelligence (AAAI) (CCF Rank A), 2019, pp. 5353-5360.

[6]. Yuying Xing+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Zili Zhang, Maozu Guo Multi-View Multi-Instance Multi-Label Learning based on Collaborative Matrix Factorization, 33rd AAAI Conference on Artificial Intelligence (AAAI) (CCF Rank A),2019, pp. 5508-5515.

[7]. Xuanwu Liu+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Yazhou Ren, Maozu Guo Ranking-based Deep Cross-modal Hashing, 33rd AAAI Conference on Artificial Intelligence (AAAI) (CCF Rank A), 2019, pp. 4400-4407.

[8]. Xuanwu Liu, Zhao Li, Jun Wang, Guoxian Yu*, Carlotta Domeniconi, Xiangliang Zhang. Cross-modal Zero-shot Hashing , IEEE International Conference on Data Mining (ICDM) (CCF B), 2019, pp. 449-458.

[9]. Shixin Yao+, Guoxian Yu, Xing Wang, Jun Wang*, Carlotta Domeniconi, Maozu Guo Discovering Multiple Co-Clusterings in Subspaces, SIAM Conference on Data Mining (SDM) (CCF Rank B), 2019, pp. 423-431.

[10]. Yuehui Wang+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Xiangliang Zhang, Maozu Guo. Selective Matrix Factorization for Multi-Relational Data Fusion, 24th International Conference on Database Systems for Advanced Applications (DASFAA) (CCF Rank B), 2019, pp. 313-329.

[11]. Yuying Xing+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Zili Zhang. Multi-Label Co-Training, 27th International Joint Conference on Artificial Intelligence (IJCAI) (CCF Rank A), 2018, pp.2882-2888.

[12]. Qiaoyu Tan+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Zili Zhang. Incomplete Multi-View Weak-Label Learning, 27th International Joint Conference on Artificial Intelligence (IJCAI) (CCF Rank A), 2018, pp.2703-2709.

[13]. Jinzheng Tu+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Guoqiang Xiao, and Maozu Guo. Multi-Label Answer Aggregation based on Joint Matrix Factorization, International Conference on Data Mining (ICDM) (CCF Rank B), 2018, pp.517-526.

[14]. Xing Wang+, Guoxian Yu, Carlotta Domeniconi, Jun Wang*, Zhiwen Yu, and Zili Zhang. Multiple Co-Clusterings, International Conference on Data Mining (ICDM) (CCF Rank B), 2018, pp. 1308-1313.

[15]. Xia Chen+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Zhao Li, and Zili Zhang. Cost Effective Multi-label Active Learning via Querying Subexamples, International Conference on Data Mining (ICDM) (CCF Rank B), 2018, pp. 905-910.

[16]. Guoxian Yu*, Xia Chen+, Carlotta Domeniconi, Jun Wang, Zhao Li, Zili Zhang, and Xindong Wu. Feature-induced Partial Multi-label Learning, International Conference on Data Mining (ICDM) (CCF Rank B), 2018, pp. 1398-1403.

[17]. Qiaoyu Tan+, Guoxian Yu*, Jun Wang, Zili Zhang, Carlotta Domeniconi. Multi-view Weak-label Learning based on Matrix Completion, 18th SIAM Conference on Data Mining (SDM) (CCF Rank B), 2018, pp. 450-458.

[18]. Xia Chen+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Zili Zhang. Matrix Factorization for Identifying Noisy Labels of Multi-label Instances, 15th Pacific Rim International Conference on Artificial Intelligence (PRICAI) (CCF Rank C), 2018, pp. 508-517

[19]. Yanming Yu+, Guoxian Yu*, Xia Chen+ and Yazhou Ren. Semi-supervised Multi-label Linear Discriminant Analysis, 24th International Conference on Neural Information Processing (ICONIP) (CCF Rank C), 2017, pp. 688-698.

[20]. Guoxian Yu*, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zili Zhang. Protein Function Prediction by Integrating Multiple Kernels, 23rd International Joint Conference on Artificial Intelligence (IJCAI) (CCF Rank A), 2013, pp.1869-1875.

[21]. Guoxian Yu*, Carlotta Domeniconi, Huzefa Rangwala, Guoji Zhang. Protein Function Prediction using Dependence Maximization, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD) (CCF Rank B), 2013, pp. 574-589.

[22]. Guoxian Yu*, Carlotta Domeniconi, Huzefa Rangwala, Guoji Zhang, Zhiwen Yu. Transductive Multi-label Ensemble Classification for Protein Function Prediction, Proceedings of the 18th ACM SIGKDD Conference on Knowledge Discovery in Database (KDD) (CCF Rank A), 2012, pp. 1077-1085.


国际期刊论文

[1]. Xianxue Yu+, Guoxian Yu*, Jun Wang, Carlotta Domeniconi. Co-clustering Ensembles based on Multiple Relevance Measures, IEEE Transactions on Knowledge and Data Engineering (CCF Rank A), In Print.

[2]. Jun Wang, Xing Wang+, Guoxian Yu*, Carlotta Domeniconi, Zhiwen Yu, Zili Zhang. Discovering Multiple Co-Clusterings with Matrix Factorization, IEEE Transactions on Cybernetics (CCF Rank B), In Print.

[3]. Qiaoyu Tan+, Guoxian Yu*, Jun Wang, Carlotta Domeniconi, Xiangliang Zhang. Individuality and Commonality based Multi-View Multi-Label Learning, IEEE Transactions on Cybernetics (CCF Rank B), In Print.

[4]. Xuanwu Liu+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Guoqiang Xiao, Maozu Guo. Weakly-supervised Cross-modal Hashing, IEEE Transactions on Big Data (CCF Rank C), In Print.

[5]. Jun Wang, Ziying Yang+, Carlotta Domeniconi, Xiangliang Zhang, Guoxian Yu*. Cooperative driver pathway discovery via fusion of multi-relational data of genes, miRNAs, and pathways, Briefings in Bioinformatics (CCF Rank B), In Print.

[6]. Keyao Wang+, Jun Wang, Carlotta Domeniconi, Xiangliang Zhang, Guoxian Yu*. Differentiating isoform functions with collaborative matrix factorization, Bioinformatics (CCF Rank B), In Print.

[7]. Guoxian Yu, Keyao Wang+, Carlotta Domeniconi, Maozu Guo*, Jun Wang*. Isoform function prediction based on bi-random walks on a heterogeneous network, Bioinformatics (CCF Rank B), In Print.

[8]. Guoxian Yu*, Yuan Jiang, Jun Wang, Hao Zhang, Haiwei Luo*. BMC3C: Binning Metagenomic Contigs using Codon usage, sequence Composition and read Coverage, Bioinformatics (CCF Rank B), 2018, 34(24): 4171-4179. 

[9]. Guangyuan Fu+, Jun Wang, Carlotta Domeniconi, Guoxian Yu*. Matrix factorization based data fusion for the prediction of lncRNA-disease associations, Bioinformatics (CCF Rank B), 2018, 34(9): 1529-1537.

[10]. Guangyuan Fu+, Jun Wang, Bo Yang, Guoxian Yu*. NegGOA: Negative GO Annotations Selection using Ontology Structure, Bioinformatics (CCF Rank B), 2016, 32(19): 2996-3004.

[11]. Yingwen Zhao+, Jun Wang, Maozu Guo, Xiangliang Zhang, Guoxian Yu*. Cross-Species Protein Function Prediction with Asynchronous-Random Walk, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF RankB), In Print.

[12]. Ziying Yang+, Guoxian Yu, Maozu Guo, Jiantao Yu, Xiangliang Zhang, Jun Wang*. CDPath: Cooperative driver pathways discovery using integer linear programming and Markov clustering, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF Rank B), In Print.

[13]. Guoxian Yu, Keyao Wang+, Guangyuan Fu, Maozu Guo, Jun Wang*. NMFGO: Gene function prediction via nonnegative matrix factorization with Gene Ontology, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF Rank B), In Print.

[14]. Guoxian Yu*, Guangyuan Fu+, Jun Wang, Yingwen Zhao+. NewGOA: predicting new GO annotations of proteins by bi-random walks on a hybrid graph, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF Rank B), 2018, 15(4): 1390-1402.

[15]. Guoxian Yu*, Guangyuan Fu+, Jun Wang, Hailong Zhu. Predicting Protein Function via Semantic Integration of Multiple Networks, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF Rank B), 2016, 13(2): 220-232.

[16]. Guoxian Yu*, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zili Zhang. Predicting Protein Function using Multiple Kernels, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF Rank B), 2015, 12(1): 219-233.

[17]. Guoxian Yu*, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zhiwen Yu. Protein Function Prediction with Incomplete Annotations, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF Rank B), 2014, 11(3): 579-591.

[18]. Guoxian Yu*, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zhiwen Yu. Protein Function Prediction using Multi-label Ensemble Classification, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF Rank B), 2013, 10(4): 1045-1057.

[19]. Jinzheng Tu+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Guoqiang Xiao, Maozu Guo. Multi-Label Crowd Consensus via Joint Matrix Factorization, Knowledge and Information Systems (CCF Rank B), In Print.

[20]. Guoxian Yu*, Guoji Zhang, Zili Zhang, Zhiwen Yu, Lin Deng. Semi-Supervised Classification based on Subspace Sparse Representation, Knowledge and Information Systems (CCF Rank B), 2015, 43 (1): 81-101.

[21]. Guoxian Yu*, Guoji Zhang, Carlotta Domeniconi, Zhiwen Yu and Jane You. Semi-Supervised Classification based on Random Subspace Dimensionality Reduction, Pattern Recognition (CCF Rank B), 2012, 45(3): 1119-1135.

[22]. Yuehui Wang+, Maozu Guo, Yazhou Ren, Lianyin Jia, Guoxian Yu*. Drug Repositioning based on Individual Bi-random Walks on a Heterogeneous Network, BMC Bioinformatics (CCF Rank C), In Print.

[22]. Guoxian Yu*, Chang Lu+, Jun Wang. NoGOA: predicting noisy GO annotations using evidences and sparse representation, BMC Bioinformatics (CCF Rank C), 2017, 18: 350.

[23]. Guoxian Yu*, Hailong Zhu, Carlotta Domeniconi. Predicting Protein Function using Incomplete Hierarchical Labels, BMC Bioinformatics (CCF Rank C), 2015, 16: 1.

[24]. Guoxian Yu*, Hailong Zhu, Carlotta Domeniconi, Jiming Liu. Predicting protein function via downward random walks on a gene ontology, BMC Bioinformatics (CCF Rank C), 2015, 16: 271.

[25]. Guoxian Yu*, Wei Luo, Guangyuan Fu, Jun Wang. Interspecies gene function prediction using semantic similarity, BMC Systems Biology, 2016, 10: 361.

[26]. Guoxian Yu*, Hailong Zhu, Carlotta Domeniconi, Maozu Guo. Integrating Multiple Networks for Protein Function Prediction, BMC Systems Biology, 2015, 9(S1): S3.

[27]. Xia Chen+, Guoxian Yu*, Qiaoyu Tan, Jun Wang. Weighted Samples based Semi-Supervised Classification, Applied Soft Computing, 2019, 79: 46-58.

[28]. Jun Wang, Guangjun Yao, Guoxian Yu*. Semi-supervised classification by discriminative regularization, Applied Soft Computing, 2017, 58: 245-255.

[29]. Guoxian Yu*, Guoji Zhang, Zhiwen Yu, Carlotta Domeniconi, Jane You, Guoqiang Han. Semi-Supervised Ensemble Classification in Subspaces, Applied Soft Computing, Applied Soft Computing, 2012, 12(5): 1511-1522.

[30]. Yuehui Wang+, Guoxian Yu*, Jun Wang, Guangyuan Fu, Maozu Guo, Carlotta Domeniconi. Weighted Matrix Factorization on multi-relational data for LncRNA-Disease Association prediction, Methods, In Print.

[31]. Yingwen Zhao+, Guangyuan Fu+, Jun Wang, Maozu Guo, Guoxian Yu*. Gene function prediction based on Gene Ontology Hierarchy Preserving Hashing, Genomics, 2019, 111(3): 334-342.

[32]. Qiaoyu Tan+, Yezi Liu, Xia Chen, Guoxian Yu*. Multi-Label Classification Based on Low Rank Representation for Image Annotation, Remote Sensing, 2017, 9(2): 109.

[33]. Guoxian Yu*, Guangyuan Fu+, Chang Lu+, Yazhou Ren, Jun Wang*. BRWLDA: Bi-random walks for predicting lncRNA-disease associations, Oncotarget, 2017, 8(36): 60429-60446.

[34]. Guoxian Yu, Yingwen Zhao+, Chang Lu+, Jun Wang*. HashGO: Hashing Gene Ontology for protein function prediction, Computational Biology and Chemistry, 2017, 71: 264-273.

[35]. Chang Lu+, Jun Wang, Zili Zhang, Pengyi Yang, Guoxian Yu*. NoisyGOA: Noisy GO annotations prediction using taxonomic and semantic similarity, Computational Biology and Chemistry, 2016, 65: 203-211.

[36]. Guoxian Yu*, Hong Peng, Jia Wei, Qianli Ma, Enhanced Locality Preserving Projections with Robust Path based Similarity, Neurocomputing (CCF Rank C), 2011, 74(4): 598-605.                

指导学生获奖

[1].2019.12 普京游戏大厅首届研究生优秀导学团队

[2].2019.10 研究生国家奖学金(刑玉莹,王越辉,曹霞,屠金政,刘玄武,杨子影,姚世新)

[3].2019.07 重庆市优秀毕业生(陈霞)

[4].2019.03 重庆市优秀硕士学位论文(路畅)

[5].2019.03 美国大学生数学建模M奖(王梦宁), H奖(刘怡君,陈聪)

[6].2018.06 普京游戏网站优秀导学团队(机器学习与数据分析实验室)一等奖

[7].2018.06 重庆市优秀毕业生(傅广垣), 重庆市研究生创新项目(陈霞)

[8].2017.12 全国研究生数学建模二等奖(傅广垣,陈霞, 赵颖闻), 三等奖(杨子影, 刘玄武, 严扬洋)

[9].2017.09 研究生国家奖学金(傅广垣,余显学,江源,陈霞), 普京游戏大厅一等奖学金(全体研究生)

[10].2017.05 普京游戏网站优秀导学团队(机器学习与数据分析实验室)

[11].2016.11全国研究生数学建模一等奖(江源,陈霞, 张龙),二等奖(刘捷, 余显学, 姜琳)

[12].2016.10研究生国家奖学金(傅广垣, 路畅), 普京游戏大厅一等奖学金(全体研究生)

[13].2016.07重庆市研究生创新项目(傅广垣)

[14]. 2016.05国家大学生创新创业训练计划项目(谭桥宇, 郁颜铭)

[15]. 2015.08中国机器学习会议优秀学生论文奖(傅广垣)


备注

欢迎对机器学习,数据挖掘,生物信息学,大数据挖掘和深度学习等研究方向和平台感兴趣的研究生(+本科生)加入我们的研究队伍。我们为同学们提供发表高水平科研与应用成果的精细指导,实验平台和优良学术氛围,为同学们提供争取各种国家和学校学院奖学金和创新项目、参加各种国内外相关竞赛奖项的机会,为同学们提供去往国内外知名高校(清华大学、哈尔滨工业大学、香港中文大学、美国、澳洲和欧洲多所合作大学)深造的机会,去往国内知名IT企业和研究所(阿里、腾讯、百度等)实习交流的机会,欢迎喜欢科学研究与项目实践的同学加入我们的研究团队

欢迎访问我们团队主页: http://mlda.swu.edu.cn/ 了解更多团队情况。

 

邮件是联系我的最佳方式:gxyu@swu.edu.cn; guoxian85@gmail.com,我会尽快回复你的邮件。


 

发布时间:2016-04-28 来源:本站原创 作者:本站编辑   浏览次数:
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