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Robi Polikar: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Jeffrey Byorick, Robi Polikar
    Confidence Estimation Using the Incremental Learning Algorithm, Learn++. [Citation Graph (0, 0)][DBLP]
    ICANN, 2003, pp:181-188 [Conf]
  2. Zeki Erdem, Robi Polikar, Fikret S. Gürgen, Nejat Yumusak
    Reducing the Effect of Out-Voting Problem in Ensemble Based Incremental Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    ICANN (2), 2005, pp:607-612 [Conf]
  3. Hussein Syed Mohammed, James Leander, Matthew Marbach, Robi Polikar
    Can AdaBoost.M1 Learn Incrementally? A Comparison to Learn++ Under Different Combination Rules. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2006, pp:254-263 [Conf]
  4. Zeki Erdem, Robi Polikar, Nejat Yumusak, Fikret S. Gürgen
    Classification of Volatile Organic Compounds with Incremental SVMs and RBF Networks. [Citation Graph (0, 0)][DBLP]
    ISCIS, 2005, pp:322-331 [Conf]
  5. Zeki Erdem, Robi Polikar, Fikret S. Gürgen, Nejat Yumusak
    Ensemble of SVMs for Incremental Learning. [Citation Graph (0, 0)][DBLP]
    Multiple Classifier Systems, 2005, pp:246-256 [Conf]
  6. Michael Lewitt, Robi Polikar
    An Ensemble Approach for Data Fusion with Learn++. [Citation Graph (0, 0)][DBLP]
    Multiple Classifier Systems, 2003, pp:176-185 [Conf]
  7. Michael Muhlbaier, Apostolos Topalis, Robi Polikar
    Learn++.MT: A New Approach to Incremental Learning. [Citation Graph (0, 0)][DBLP]
    Multiple Classifier Systems, 2004, pp:52-61 [Conf]
  8. Michael Muhlbaier, Apostolos Topalis, Robi Polikar
    Ensemble Confidence Estimates Posterior Probability. [Citation Graph (0, 0)][DBLP]
    Multiple Classifier Systems, 2005, pp:326-335 [Conf]
  9. Devi Parikh, Min T. Kim, Joseph Oagaro, Shreekanth Mandayam, Robi Polikar
    Combining classifiers for multisensor data fusion. [Citation Graph (0, 0)][DBLP]
    SMC (2), 2004, pp:1232-1237 [Conf]
  10. Robi Polikar, L. Upda, S. S. Upda, Vasant Honavar
    Learn++: an incremental learning algorithm for supervised neural networks. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Systems, Man, and Cybernetics, Part C, 2001, v:31, n:4, pp:497-508 [Journal]
  11. Michael Muhlbaier, Robi Polikar
    An Ensemble Approach for Incremental Learning in Nonstationary Environments. [Citation Graph (0, 0)][DBLP]
    MCS, 2007, pp:490-500 [Conf]
  12. Joseph DePasquale, Robi Polikar
    Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features. [Citation Graph (0, 0)][DBLP]
    MCS, 2007, pp:251-260 [Conf]

  13. Margin-based discriminant dimensionality reduction for visual recognition. [Citation Graph (, )][DBLP]


  14. Functional Near-Infrared Spectroscopy and Electroencephalography: A Multimodal Imaging Approach. [Citation Graph (, )][DBLP]


  15. Nearest hyperdisk methods for high-dimensional classification. [Citation Graph (, )][DBLP]


  16. Incremental learning in non-stationary environments with concept drift using a multiple classifier based approach. [Citation Graph (, )][DBLP]


  17. Random Feature Subset Selection for Analysis of Data with Missing Features. [Citation Graph (, )][DBLP]


  18. Ensemble Based Data Fusion from Parietal Region Event Related Potentials for Early Diagnosis of Alzheimer's Disease. [Citation Graph (, )][DBLP]


  19. Ensemble Techniques with Weighted Combination Rules for Early Diagnosis of Alzheimer's Disease. [Citation Graph (, )][DBLP]


  20. Learning concept drift in nonstationary environments using an ensemble of classifiers based approach. [Citation Graph (, )][DBLP]


  21. Incremental Learning of Variable Rate Concept Drift. [Citation Graph (, )][DBLP]


  22. Incremental Learning of New Classes in Unbalanced Datasets: Learn + + .UDNC. [Citation Graph (, )][DBLP]


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