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个人简介

简介 最优化与人工智能研究小组成员(http://www.optimal-group.org/),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 2012-2013,吉林大学研究生创新基金(20121053),已结题; 2015-2017,内蒙古自然科学基金博士基金(2015BS0606),优秀结题; 2016-2018,国家自然科学基金青年基金(11501310),已结题; 2019-2020,内蒙古青年科技英才入选者(NJYT-19-B01),已结题; 2019-2022,内蒙古自然科学基金面上基金(2019MS06008) 2020-2021,符号计算与知识工程教育部重点实验室开放基金(93K172020K02) 2020-2023,国家自然科学基金地区基金(61966024)

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近期论文

查看导师最新文章 (温馨提示:请注意重名现象,建议点开原文通过作者单位确认)

[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: 2267–2277. (SCI二区)

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