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Ji Zhu: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. David Abramson, Amanda Lynch, Hiroshi Takemiya, Yusuke Tanimura, Susumu Date, Haruki Nakamura, Karpjoo Jeong, Suntae Hwang, Ji Zhu, Zhonghua Lu, Céline Amoreira, Kim Baldridge, Hurng-Chun Lee, Chi-Wei Wang, Horng-Liang Shih, Tomas E. Molina, Wilfred W. Li, Peter W. Arzberger
    Deploying Scientific Applications to the PRAGMA Grid Testbed: Strategies and Lessons. [Citation Graph (0, 0)][DBLP]
    CCGRID, 2006, pp:241-248 [Conf]
  2. Ji Zhu, Ang Guo, Zhonghua Lu, Yongwei Wu, Bin Shen, Xuebin Chi
    Analysis of the Bioinformatics Grid Technique Applications in China. [Citation Graph (0, 0)][DBLP]
    CCGRID, 2006, pp:44- [Conf]
  3. Ira Pramanick, James Mauro, Ji Zhu
    A System Recovery Benchmark for Clusters. [Citation Graph (0, 0)][DBLP]
    CLUSTER, 2003, pp:387-394 [Conf]
  4. Ji Zhu, James Mauro, Ira Pramanick
    Robustness Benchmarking for Hardware Maintenance Events. [Citation Graph (0, 0)][DBLP]
    DSN, 2003, pp:115-122 [Conf]
  5. Dong Tang, Ji Zhu, Roy Andrada
    Automatic Generation of Availability Models in RAScad. [Citation Graph (0, 0)][DBLP]
    DSN, 2002, pp:488-494 [Conf]
  6. Li Wang, Michael D. Gordon, Ji Zhu
    Regularized Least Absolute Deviations Regression and an Efficient Algorithm for Parameter Tuning. [Citation Graph (0, 0)][DBLP]
    ICDM, 2006, pp:690-700 [Conf]
  7. Zhili Wu, Chun-hung Li, Ji Zhu, Jian Huang
    A Semi-supervised SVM for Manifold Learning. [Citation Graph (0, 0)][DBLP]
    ICPR (2), 2006, pp:490-493 [Conf]
  8. Ji Zhu, Trevor Hastie
    Support Vector Machines, Kernel Logistic Regression and Boosting. [Citation Graph (0, 0)][DBLP]
    Multiple Classifier Systems, 2002, pp:16-26 [Conf]
  9. Lacey Gunter, Ji Zhu
    Computing the Solution Path for the Regularized Support Vector Regression. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  10. Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu
    The Entire Regularization Path for the Support Vector Machine. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  11. Saharon Rosset, Ji Zhu, Trevor Hastie
    Margin Maximizing Loss Functions. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  12. Saharon Rosset, Ji Zhu, Hui Zou, Trevor Hastie
    A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  13. Ji Zhu, Trevor Hastie
    Kernel Logistic Regression and the Import Vector Machine. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:1081-1088 [Conf]
  14. Ji Zhu, Saharon Rosset, Trevor Hastie, Robert Tibshirani
    1-norm Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  15. James Mauro, Ji Zhu, Ira Pramanick
    The System Recovery Benchmark. [Citation Graph (0, 0)][DBLP]
    PRDC, 2004, pp:271-280 [Conf]
  16. Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu
    The Entire Regularization Path for the Support Vector Machine. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2004, v:5, n:, pp:1391-1415 [Journal]
  17. Saharon Rosset, Ji Zhu, Trevor Hastie
    Boosting as a Regularized Path to a Maximum Margin Classifier. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2004, v:5, n:, pp:941-973 [Journal]
  18. Lacey Gunter, Ji Zhu, Susan Murphy
    Variable Selection for Optimal Decision Making. [Citation Graph (0, 0)][DBLP]
    AIME, 2007, pp:149-154 [Conf]
  19. Saharon Rosset, Grzegorz Swirszcz, Nathan Srebro, Ji Zhu
    l1 Regularization in Infinite Dimensional Feature Spaces. [Citation Graph (0, 0)][DBLP]
    COLT, 2007, pp:544-558 [Conf]
  20. Li Wang, Ji Zhu, Hui Zou
    Hybrid huberized support vector machines for microarray classification. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:983-990 [Conf]
  21. Sijian Wang, Ji Zhu
    Improved centroids estimation for the nearest shrunken centroid classifier. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2007, v:23, n:8, pp:972-979 [Journal]

  22. Boosting and support vector machines as optimal separators. [Citation Graph (, )][DBLP]


  23. Pathway Detection Based on Hierarchical LASSO Regression Model. [Citation Graph (, )][DBLP]


  24. Analysis of array CGH data for cancer studies using fused quantile regression. [Citation Graph (, )][DBLP]


  25. Hybrid huberized support vector machines for microarray classification and gene selection. [Citation Graph (, )][DBLP]


  26. REMAS: a new regression model to identify alternative splicing events from exon array data. [Citation Graph (, )][DBLP]


  27. The Missing Piece Syndrome in Peer-to-Peer Communication [Citation Graph (, )][DBLP]


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