余国先

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



姓名:余国先性别:
学历:博士 职称:副教授
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
湖北孝感人,工学博士,副教授,硕士生导师,

IEEE数据挖掘与大数据分析技术委员会委员(IEEE Data Mining and Big Data Analytics Technical Committee),

CCF生物信息学专业组委员,大数据专委会通讯委员,人工智能与模式识别专委会委员;人工智能学会生物信息学与人工生命专委会委员。

2013-至今 西南大学计算机与信息科学学院从事教学科研工作
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

Google Scholar, DBLP; 机器学习与数据分析实验室主页:https://mlda.swu.edu.cn/

主要研究方向:机器学习,数据挖掘及生物信息学等。
主持的项目:国家自然科学基金,留学人员科技活动择优资助项目(已结题),
重庆市基础与前沿研究项目(已结题),教育部重点实验室开放项目(已结题),
中央高校基本业务费重点项目(已结题),西南大学研究生院跨学科学术沙龙项目,西南大学教改项目(重点)。
已完成中央高校基本业务费一般项目和博士启动项目各一项

近年来,在国际顶级会议(SIGKDD, IJCAI, ECML/PKDD, ICDM等), 国内外知名期刊
(Bioinformatics, IEEE/ACM Trans. on Computational Biology and Bioinformatics,
BMC Bioinformatics, BMC Systems Biology, Knowledge and Information Systems,
Pattern Recognition, Neurocomputing,中国科学-信息科学,软件学报,计算机研究与发展等)发表论文40多篇.

KDD16, ICDM14-16, SDM14-18, CIDM14-16, CCFAI17, CCFBigData15-17, CBC16-17PC(Program Committee),

IEEE/ACM Trans. on Computational Biology and Bioinformatics, Information Fusion, Neurocomputing,

自动化学报和中国科学-信息科学等国内外期刊的审稿人.

教学情况
本科生:数据库原理导论;Matlab程序设计与实践; Java程序设计
研究生: 机器学习;数据挖掘
西南大学含弘学院专业导师
论文情况

Selected Publications: (+ indicates supervised student,* indicates corresponding author)

会议论文:

[1].   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 (Knowledge Discovery and Data Mining), 2012. CCF推荐A类国际会议

[2].   Guoxian Yu*Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zili Zhang. Protein function prediction by integrating multiple kernels, Proceedings of the 23rd IJCAI (International Joint Conference on Artificial Intelligence), 2013. CCF推荐A类国际会议

[3].   Guoxian Yu*,  Carlotta Domeniconi, Huzefa Rangwala, Guoji Zhang. Protein function prediction using dependence maximization, Proceedings of the ECML/PKDD(23rd European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases), 2013. CCF推荐B类国际会议

[4].   Yazhou Ren, Carlotta Domeniconi, Guoji Zhang, Guoxian Yu. Weighted-object ensemble clustering. Proceedings of IEEE International Conference on Data Mining (ICDM), 2013. CCF推荐B类国际会议

[5].   Yazhou Ren, Carlotta Domeniconi, Guoji Zhang, Guoxian Yu. A weighted adaptive mean shift clustering algorithm. SIAM Conference on Data Mining (SDM), 2014. CCF推荐B类国际会议

[6].   Yanming Yu+, Guoxian Yu*, Xia Chen+, Yazhou Ren. Semi-supervised multi-label linear discriminant analysis, 24th International Conference on Neural Information Processing (ICONIP), 2017. In Print. CCF推荐C类国际会议

[7].   Guoxian Yu*, Zhiwen Yu, Jing Hua, Xuan Li and Jane You. Sparse representation based spectral regression, in Proceedings of the IEEE 10th International Conference on Machine Learning and Cybernetics (ICMLC), 2011, pp. 532-537.  Best Student Paper (2/500), ICMLC最佳学生论文奖.


期刊论文

[8].   Guangyuan Fu+, Jun Wang, Bo Yang, Guoxian Yu*. NegGOA: Negative GO annotations selection using Ontology structure.  Bioinformatics, 32(19): 2996-3004, 2016. CCF推荐B类综合期刊

[9].   Guoxian Yu*, Guoji Zhang, Carlotta Domeniconi, Zhiwen Yu and Jane You. Semi-supervised classification based on random subspace dimensionality reduction. Pattern Recognition, 45 (3): 1119-1135, 2012. CCF 推荐B类国际期刊

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

[11].Zhiwen Yu, Hau-San Wong, Jane You, Guoxian Yu and Guoqiang Han. Hybrid cluster ensemble framework based on the random combination of data transformation operators. Pattern Recognition, 45 (5):1826-1837, 2012. CCF推荐B类国际期刊.

[12].Zhiwen Yu, Le Li, Hau-San Wong, Jane You, Guoqiang Han, Yunjun Guo, Guoxian Yu. Probabilistic cluster structure ensemble. Information Sciences, 267: 16–34, 2014. CCF推荐B类国际期刊

[13].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 (TCBB), In Print. CCF推荐C类国际期刊

[14].Guoxian Yu*, Guangyuan Fu+, Jun Wang, Hailong Zhu. Protein function prediction via semantic integration of multiple networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 13(2): 220-232, 2016. CCF推荐C类综合期刊

[15].Guoxian Yu*, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zili Zhang. Predicting protein function using multiple kernels. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 12 (1): 219-233, 2015. CCF推荐C类综合期刊

[16].Guoxian Yu*, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zhiwen Yu, Protein function prediction with incomplete annotations, IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 11 (3): 579-591, 2014. CCF推荐C类综合期刊

[17].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 (TCBB), 10 (4): 1045-1057, 2013. CCF推荐C类综合期刊

[18].Guoxian Yu*, Chang Lu+, Jun Wang. NoGOA: predicting noisy GO annotations using evidences and sparse representation. BMC Bioinformatics, 18: 350, 2017. CCF推荐C类国际期刊

[19].Guoxian Yu*, Hailong Zhu*, Carlotta Domeniconi, Jiming Liu. Predicting protein function via downward random walks on a gene ontology. BMC Bioinformatics, 16: 271, 2015. CCF推荐C类国际期刊

[20].Guoxian Yu*, Hailong Zhu, Carlotta Domeniconi, Predicting protein function using incomplete hierarchical labels. BMC Bioinformatics, 16: 1, 2015. CCF推荐C类综合期刊

[21].Guoxian Yu*, Hong Peng, Jia Wei and Qianli Ma. Enhanced locality preserving projections with robust path based similarity. Neurocomputing, 74 (4): 598-605, 2011. CCF 推荐C类国际期刊

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

[23].Guoxian Yu*, Hailong Zhu, Carlotta Domeniconi, Maozu Guo. Integrating multiple networks for protein function prediction. BMC Systems Biology, Vol. 9(S1): S3, 2015.

[24].Qiaoyu Tan+, Yanming Yu+, Guoxian Yu, Jun Wang*. Semi-supervised multi-label classification using incomplete label information. Neurocomputing, 260: 192-202, 2017. CCF推荐C类期刊

[25].Yazhou Ren, Guoji Zhang, Guoxian Yu, Xuan Li. Local and global structure preserving based feature selection, Neurocomputing, 89: 147-157, 2012. CCF 推荐C类国际期刊

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

[27].Guoxian Yu, Guoji Zhang, Zhiwen Yu*, Carlotta Domeniconi, Jane You and Guoqiang Han, Semi-supervised ensemble classification in subspaces, Applied Soft Computing, 12 (5): 1511-1522, 2012.

[28].Qiaoyu Tan+, Yezi Liu, Xia Chen+, Guoxian Yu*. Multi-label classification based on low rank representation for image annotation. Remote Sensing, 9(2), 109, 2017.

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

[30].Jie Liu+, Guoxian Yu, Yuan Jiang+, Jun Wang*. HiSeeker: detecting high-order SNP interactions based on pairwise SNP combinations. Genes, 8: 153, 2017.

[31].Yanmin Yu+, Jun Wang*, Qiaoyu Tan+, Lianyin Jia, Guoxian Yu. Semi-supervised Multi-label dimensionality reduction based on dependence maximization. IEEE ACCESS, In Print.


国内期刊论文 

[32].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, In Print.

[33].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46(4):461-465, 2016. 15届中国机器学习会议优秀学生论文奖

[34].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, 54(12): xxx-xxx, 2017.

[35].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, 53(8): 1753-1765, 2016.

[36].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, 28(11): xxx-xxx, 2017.




指导学生获奖

[1]. 2017.09研究生国家奖学金(傅广垣,余显学,江源,陈霞)

[2]. 2017.05计算机与信息科学学院优秀导学团队(机器学习与数据分析实验室)

[3]. 2017.04中央高校基本业务科研费-学生项目(傅广垣,陈霞,刘捷)

[4]. 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)

[5]. 2016.10研究生国家奖学金(傅广垣, 路畅)

[6]. 2016.07重庆市研究生创新项目(傅广垣)

[7]. 2016.05国家大学生创新创业训练计划项目(谭桥宇, 郁颜铭)

[8]. 2016.04西南大学计信院创新基金一等资助(路畅),二等资助(傅广垣)

[9]. 2016.04中央高校基本业务科研费-学生项目(路畅, 傅广垣)

[10]. 2015.12西南大学校创项目(谭桥宇, 郁颜铭, 涂欢)

[11]. 2015.11全国研究生数学建模三等奖2(路畅,罗卫;江源,刘捷,王贵军)

[12]. 2015.08中国机器学习会议优秀学生论文奖(傅广垣)

[13]. 2014.11全国研究生数学建模三等奖1(路畅,姚光军)


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