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Vladimir Vapnik: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Isabelle Guyon, Nada Matic, Vladimir Vapnik
    Discovering Informative Patterns and Data Cleaning. [Citation Graph (1, 0)][DBLP]
    KDD Workshop, 1994, pp:145-156 [Conf]
  2. Bernhard E. Boser, Isabelle Guyon, Vladimir Vapnik
    A Training Algorithm for Optimal Margin Classifiers. [Citation Graph (0, 0)][DBLP]
    COLT, 1992, pp:144-152 [Conf]
  3. Jinbo Bi, Vladimir Vapnik
    Learning with Rigorous Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    COLT, 2003, pp:243-257 [Conf]
  4. Vladimir Vapnik
    Inductive Principles of the Search for Empirical Dependences (Methods Based on Weak Convergence of Probability Measures). [Citation Graph (0, 0)][DBLP]
    COLT, 1989, pp:3-21 [Conf]
  5. Volker Blanz, Bernhard Schölkopf, Heinrich H. Bülthoff, Chris Burges, Vladimir Vapnik, Thomas Vetter
    Comparison of View-Based Object Recognition Algorithms Using Realistic 3D Models. [Citation Graph (0, 0)][DBLP]
    ICANN, 1996, pp:251-256 [Conf]
  6. Klaus-Robert Müller, Alex J. Smola, Gunnar Rätsch, Bernhard Schölkopf, Jens Kohlmorgen, Vladimir Vapnik
    Predicting Time Series with Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    ICANN, 1997, pp:999-1004 [Conf]
  7. Bernhard Schölkopf, Chris Burges, Vladimir Vapnik
    Incorporating Invariances in Support Vector Learning Machines. [Citation Graph (0, 0)][DBLP]
    ICANN, 1996, pp:47-52 [Conf]
  8. Vladimir Vapnik
    The Support Vector Method. [Citation Graph (0, 0)][DBLP]
    ICANN, 1997, pp:263-271 [Conf]
  9. Harris Drucker, Corinna Cortes, Lawrence D. Jackel, Yann LeCun, Vladimir Vapnik
    Boosting and Other Machine Learning Algorithms. [Citation Graph (0, 0)][DBLP]
    ICML, 1994, pp:53-61 [Conf]
  10. Vladimir Vapnik
    Statistical Theory of Generalization (Abstract). [Citation Graph (0, 0)][DBLP]
    ICML, 1996, pp:557- [Conf]
  11. Jason Weston, Ronan Collobert, Fabian H. Sinz, Léon Bottou, Vladimir Vapnik
    Inference with the Universum. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:1009-1016 [Conf]
  12. Asa Ben-Hur, Hava T. Siegelmann, David Horn, Vladimir Vapnik
    A Support Vector Clustering Method. [Citation Graph (0, 0)][DBLP]
    ICPR, 2000, pp:2724-2727 [Conf]
  13. Corinna Cortes, Harris Drucker, Dennis Hoover, Vladimir Vapnik
    Capacity and Complexity Control in Predicting the Spread Between Borrowing and Lending Interest Rates. [Citation Graph (0, 0)][DBLP]
    KDD, 1995, pp:51-56 [Conf]
  14. Bernhard Schölkopf, Chris Burges, Vladimir Vapnik
    Extracting Support Data for a Given Task. [Citation Graph (0, 0)][DBLP]
    KDD, 1995, pp:252-257 [Conf]
  15. Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladimir Vapnik
    A Support Vector Method for Clustering. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:367-373 [Conf]
  16. Olivier Chapelle, Vladimir Vapnik
    Model Selection for Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:230-236 [Conf]
  17. Olivier Chapelle, Vladimir Vapnik, Jason Weston
    Transductive Inference for Estimating Values of Functions. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:421-427 [Conf]
  18. Olivier Chapelle, Jason Weston, Léon Bottou, Vladimir Vapnik
    Vicinal Risk Minimization. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:416-422 [Conf]
  19. Corinna Cortes, Lawrence D. Jackel, Sara A. Solla, Vladimir Vapnik, John S. Denker
    Learning Curves: Asymptotic Values and Rate of Convergence. [Citation Graph (0, 0)][DBLP]
    NIPS, 1993, pp:327-334 [Conf]
  20. Harris Drucker, Christopher J. C. Burges, Linda Kaufman, Alex J. Smola, Vladimir Vapnik
    Support Vector Regression Machines. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:155-161 [Conf]
  21. Hans Peter Graf, Eric Cosatto, Léon Bottou, Igor Dourdanovic, Vladimir Vapnik
    Parallel Support Vector Machines: The Cascade SVM. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  22. Isabelle Guyon, Bernhard E. Boser, Vladimir Vapnik
    Automatic Capacity Tuning of Very Large VC-Dimension Classifiers. [Citation Graph (0, 0)][DBLP]
    NIPS, 1992, pp:147-155 [Conf]
  23. Isabelle Guyon, Vladimir Vapnik, Bernhard E. Boser, Léon Bottou, Sara A. Solla
    Structural Risk Minimization for Character Recognition. [Citation Graph (0, 0)][DBLP]
    NIPS, 1991, pp:471-479 [Conf]
  24. Bernhard Schölkopf, Patrice Simard, Alex J. Smola, Vladimir Vapnik
    Prior Knowledge in Support Vector Kernels. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  25. Vladimir Vapnik
    Principles of Risk Minimization for Learning Theory. [Citation Graph (0, 0)][DBLP]
    NIPS, 1991, pp:831-838 [Conf]
  26. Vladimir Vapnik, Steven E. Golowich, Alex J. Smola
    Support Vector Method for Function Approximation, Regression Estimation and Signal Processing. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:281-287 [Conf]
  27. Vladimir Vapnik, Sayan Mukherjee
    Support Vector Method for Multivariate Density Estimation. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:659-665 [Conf]
  28. Jason Weston, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf, Vladimir Vapnik
    Kernel Dependency Estimation. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:873-880 [Conf]
  29. Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso Poggio, Vladimir Vapnik
    Feature Selection for SVMs. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:668-674 [Conf]
  30. Alexander Gammerman, Katy S. Azoury, Vladimir Vapnik
    Learning by Transduction. [Citation Graph (0, 0)][DBLP]
    UAI, 1998, pp:148-155 [Conf]
  31. Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladimir Vapnik
    Support Vector Clustering. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2001, v:2, n:, pp:125-137 [Journal]
  32. Olivier Chapelle, Vladimir Vapnik, Yoshua Bengio
    Model Selection for Small Sample Regression. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2002, v:48, n:1-3, pp:9-23 [Journal]
  33. Olivier Chapelle, Vladimir Vapnik, Olivier Bousquet, Sayan Mukherjee
    Choosing Multiple Parameters for Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2002, v:46, n:1-3, pp:131-159 [Journal]
  34. Corinna Cortes, Vladimir Vapnik
    Support-Vector Networks. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1995, v:20, n:3, pp:273-297 [Journal]
  35. Isabelle Guyon, Jason Weston, Stephen Barnhill, Vladimir Vapnik
    Gene Selection for Cancer Classification using Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2002, v:46, n:1-3, pp:389-422 [Journal]
  36. Vladimir Vapnik, Olivier Chapelle
    Bounds on Error Expectation for Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:9, pp:2013-2036 [Journal]
  37. Isabelle Guyon, John Makhoul, Richard M. Schwartz, Vladimir Vapnik
    What Size Test Set Gives Good Error Rate Estimates?. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 1998, v:20, n:1, pp:52-64 [Journal]

  38. Large Margin vs. Large Volume in Transductive Learning. [Citation Graph (, )][DBLP]

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