徐增林
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教授
博士生导师
- 性别：男
- 出生日期：1980-02-06
- 学历：博士研究生毕业
- 学位：哲学博士学位
- 学科：计算机软件与理论
- 办公地点：B1-201
- 电子邮箱：c3a30ca1e5fcff2ab050b91efc190fa7e11327e6de380c8a3744bce87c02177ca280a662dc238d732240f1ecc3b6d1c83925ecd0ed71be68e907734ae891ae2c36a633fd45b5a5867df68d2855d1a9815d5c3f8c51a92057ec3ee3df66fc4ab9a4e406e7dbaeb55f6e80748ae4d196d9b070c7749836638191a94e2771813af8
访问量：
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[1]
Michael R. Lyu,
Irwin King,
Jianke Zhu,
Rong Jin,
and Zenglin Xu,
Efficient convex relaxation for transductive support vector machinepp. 1641-1648, Aug 2007.
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[2]
Michael R. Lyu,
Zenglin Xu,
Steven C. Hoi,
and Jianke Zhu,
An effective approach to 3d deformable surface tracking, In ECCV ’08: Proceedings of the 10th European Conference on Computer Vision, pp. 766-779, Aug 2008.
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[3]
Michael R. Lyu,
Irwin King,
Zenglin Xu,
and Kaizhu Huang,
Semi-supervised learning from general unlabeled data, In ICDM ’08: Proceedings of IEEE International Conference on Data Mining, pp. 273-282,
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[4]
Michael RLyu,
Irwin King,
Kaizhu Huang,
Rong Jin,
and Zenglin Xu,
Semi-supervised text categorization by active search, In CIKM ’08: Proceedings of the thirteenth ACM international conference on Information and knowledge, pp. 1517-1518, Aug 2008.
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[5]
Michael Lyu,
Irwin King,
Rong Jin,
and Zenglin Xu,
An extended level method for e cient multiple kernel learningpp. 1825-1832, Aug 2008.
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[6]
Irwin King,
Michael R. Lyu,
Jieping Ye,
Rong Jin,
and Zenglin Xu,
Non-monotonic feature selection, In ICML ’09: Proceedings of the 26th Annual International Conference on Machine Learning, pp. 1145-1152, Aug 2009.
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[7]
Errki Oja,
Zenglin Xu,
Irwin King,
and Zhirong Yang,
Zhirong Yang, Irwin King, Zenglin Xu, and Errki Ojapp. 2169-2177,
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[8]
Zhirong Yang,
Michael Lyu,
Irwin King,
Jianke Zhu,
Rong Jin,
and Zenglin Xu,
Adaptive regularization for transductive support vector machinepp. 2125-2133, Aug 2009.
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[9]
Irwin King,
Michael R. Lyu,
Rong Jin,
and Zenglin Xu,
Discriminative semi-supervised feature selection via manifold regularizationpp. 1303, Aug 2009.
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[10]
Cheng-Lin Liu,
Zenglin Xu,
Rong Jin,
and Kaizhu Huang,
Robust metric learning by smooth optimization, In UAI ’10: Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence, pp. 244-251, Aug 2010.
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[11]
Michael R. Lyu,
Irwin King,
Zenglin Xu,
and Haiqin Yang,
Online learning for group lassopp. 1191-1198, Aug 2010.
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[12]
Michael R. Lyu,
Irwin King,
Haiqin Yang,
Rong Jin,
and Zenglin Xu,
Simple and e cient multiple kernel learning by group lassopp. 1175{, Aug 2010.
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[13]
Irwin King,
Michael R. Lyu,
Shenghuo Zhu,
Rong Jin,
and Zenglin Xu,
Smooth optimization for effective multiple kernel learning, AAAI Press, Aug 2010.
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[14]
Yuan (Alan) Qi,
Feng Yan,
and Zenglin Xu,
Sparse matrix-variate t process blockmodels, AAAI Press, Aug 2011.
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[15]
Yuan (Alan) Qi,
Zenglin Xu,
and Feng Yan,
Sparse matrix-variate Gaussian process blockmodels for network modeling, In UAI ’11: Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial Intelligence, pp. 745–752, Aug 2011.
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[16]
Yuan (Alan) Qi,
Feng Yan,
and Zenglin Xu,
In nite tucker decomposition: Non-parametric Bayesian models for multiway data analysispp. 1023,
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[17]
Zenglin Xu,
Michael R. Lyu,
Irwin King,
and Shouyuan Chen,
Recovering pairwise interaction tensorAug 2013.
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[18]
Yuan (Alan) Qi,
Zenglin Xu,
and Shandian Zhe,
Joint association discovery and diagnosis of Alzheimer’s disease by supervised heterogeneous multiview learning
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[19]
Jan P. Allebach,
Zenglin Xu,
and Bin Shen,
Kernel Tapering: a Simple and E effective Approach to Sparse Kernels for Image ProcessingAug 2014.
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[20]
Youngja Park,
Ian Molloy,
Suresh N. Chari,
Zenglin Xu,
Ninghui Li,
and Christopher Gates,
Detecting Insider Information Theft Using Features from File Access LogsAug 2014.
