渐 令(Ling Jian)

中国石油大学(华东) , 副教授
研究兴趣:Numerical Optimizationdata mining & machine learning

中国石油大学(华东)统计学硕士生导师,从事机器学习与数据挖掘及相关应用领域的研究工作。

2017.5.2 our paper “Exploiting Expertise Rules for Statistical Data-Driven Modeling” is accepted by IEEE Transactions on Industrial Electronics

2017.4.13 our paper “Toward Online Node Classification on Streaming Networks” is accepted (with minor revision) by Data Mining and Knowledge Discovery

2017.3.5 our paper “Online Multi-Label Learning with Cost-Sensitive Budgeted SVM” is accepted by International Journal of Computational Science and Engineering

2016.12.3 our paper “A Chunk Updating LS-SVMs based on Block Gaussian Elimination Method” is accepted by Applied Soft Computing

2016.9.10 our paper “Toward Time-Evolving Feature Selection on Dynamic Networks” is accepted by ICDM 2016.

  1. Exploiting Expertise Rules for Statistical Data-Driven Modeling
    Ling Jian, Jundong Li, Shihua Luo. IEEE Transactions on Industrial Electronics: 2017 ,10.1109/TIE.2017.2703659 下载全文
  2. Online Multi-Label Learning with Cost-Sensitive Budgeted SVM
    Jing Liu, Zhongwen Guo, Ling Jian, Like Qiu, Xupeng Wang. International Journal of Computational Science and Engineering: 2017
  3. A chunk updating LS-SVMs based on block Gaussian elimination method
    Xiaoxin Song, Ling Jian, Yunquan Song. Applied Soft Computing: 2017 ,51(2) ,96--104 下载全文
  4. Towerd Time-Evolving Feature Selection on Dynamic Networks
    Jundong Li, Xia Hu, Ling Jian, Huan Liu. In Proceedings of 16th IEEE International Conference on Data Mining (ICDM): 2016 下载全文
  5. Budget Online Learning Algorithm for Least Squares SVM
    Ling Jian, Shuquian Shen, Jundong Li, Xijun Liang, Lei Li. IEEE Transactions on Neural Networks and Learning Systems: 2016 ,10.1109/TNNLS.2016.2574332 下载全文
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更新于:2017-05-27 08:59      累计访问量:2964

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