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严慧
2023-05-11 16:57
  • 严慧
  • 严慧 - 副教授-南京理工大学-计算机科学与工程学院-个人资料

近期热点

资料介绍

个人简历


工作经历
伊利诺伊大学芝加哥分校 2018.08-2019.08 访问学者
南京理工大学 2018.05 - 今 副教授,硕导,博导
南京理工大学 2015.05 - 2018.05 副教授,硕导
教育经历
博士 南京理工大学 计算机技术应用 2005/09-2011/03
访问学生 新加坡国立大学 计算机视觉 2010/04-2010/10
学士 南京理工大学 计算机通信 2001/09-2005/07

研究领域


多源多视角学习、在线学习、大数据分析、数据挖掘

近期论文


[1] Hui Yan, Siyu Liu, Philip S Yu. From Joint Feature Selection and Self-Representation Learning to Robust Multi-view Subspace Clustering. ICDM 2019
[2] Hui Yan, Jian Yang, Jingyu Yang. Robust joint feature weights learning framework. IEEE Trans. on Knowledge and Data Engineering, 2016, 28(5):1327-1339
[3] Hui Yan, Jian Yang. Locality preserving score for joint feature weights learning. Neural Networks, 2015, 69:126-134
[4] Hui Yan, Jian Yang . Sparse discriminative feature selection. Pattern Recognition, 2015, 48:1827-1835
[5] Hui Yan, Jian Yang. Joint Laplacian feature weights learning. Pattern Recognition, 2014, 47:1425–1432
[6 Hui Yan, JianYang. Sparse discriminative feature weights learning. Neurocomputing, 2016, 173:1936-1942
[7] Hui Yan, Jingyu Yang, Xiaotong Yuan, Shuicheng Yan. Correntropy based Feature Selection Using Binary Projection. Pattern Recognition, 44 (12), 2011, pp.2834-2842
[8] Hui Yan, Zhong Jin, Jian Yang. Sparse representation preserving for unsupervised feature selection. International Conference on Pattern Recognition, 2014, Stockholm, Sweden
[9] Guangsheng Xia, Hui Yan*, Jian Yang. Sparse preserving feature weights learning. Neurocomputing, 2016, 185:45-52
[10] Zheng Wei , Hui Yan* , Jian Yang,Jiangyu Yang. Robust Unsupervised Feature Selection by Nonnegative Sparse. International Conference on Pattern Recognition, 2016

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