王震

2016-11-29 文字:  点击:[]

姓名:王震

职称:教授(博导)

部门:信息与计算科学系

研究方向:模式识别

邮箱:wangzhen1882@126.com

简介

最优化与人工智能研究小组成员,本科、硕士、博士均毕业于吉林大学数学学院,获吉林大学优秀博士毕业生称号,主要研究方向集中于数据挖掘和机器学习中的各种前沿问题,特别是利用最优化理论和工具构建解决此类问题的关键技术。

科研项目

20122013,吉林大学研究生创新基金(20121053),已结题;

20152017,内蒙古自然科学基金博士基金(2015BS0606),优秀结题;

20162018,国家自然科学基金青年基金(11501310),已结题;

20192020,内蒙古青年科技英才入选者(NJYT-19-B01),已结题;

20192022,内蒙古自然科学基金面上基金(2019MS06008

20202021,符号计算与知识工程教育部重点实验室开放基金(93K172020K02

20202023,国家自然科学基金地区基金(61966024

发表论文

[1] Wang Z, et al. Semi-Supervised Fuzzy Clustering with Fuzzy Pairwise Constraints[J]. IEEE Transactions on Fuzzy Systems, 2021, in press. (SCI一区Top)

[2] Wang Z, et al. General plane-based clustering with distribution loss[J]. IEEE Transactions on Neural Networks and Learning Systems, 2021, in press. (SCI一区Top)

[3] Wang Z , Chen X , Li C N , et al. Ramp-based Twin Support Vector Clustering[J]. Neural Computing and Applications, 2020, 32(14): 9886-9896. (SCI二区)

[4] Wang Z, Shao Y H, Bai L, et al. Insensitive Stochastic Gradient Twin Support Vector Machines for Large Scale Problems[J]. Information Sciences, 2018, 462: 114-131. (SCI二区Top)

[5] Wang Z, Shao Y H, Bai L, et al. MBLDA: A novel multiple between-class linear discriminant analysis[J]. Information Sciences, 2016, 369: 199-220. (SCI二区Top)

[6] Wang Z, Shao Y H, Bai L, et al. Twin support vector machine for clustering[J]. IEEE Transactions on Neural Networks and Learning Systems, 2015, 26(10): 2583-2588. (SCI一区Top)

[7] Wang Z, Shao Y H, Wu T R. Proximal parametric-margin support vector classifier and its applications. Neural Computing & Applications, 2014, 24 (3-4): 755-764. (SCI三区)

[8] Wang Z, Shao Y H, Wu T R. A GA-based model selection for smooth twin parametric-margin support vector machine. Pattern Recognition, 2013, 46: 22672277. (SCI二区)

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