[Edit]

Vladimir Vapnik
(ALIAS: V. N. Vapnik, Vladimir N. Vapnik, V. Vapnik) [FOAF]  [Follow]

Position: Professor
Affiliation: Computer Science Royal Holloway
Phone: +44 1784 443673
Email:
Homepage: http://www.clrc.rhul.ac.uk/people/vlad/
[Edit]
Statistics: H-index: 34 (See all experts' h-index.)
total citation number: 17611
highest-cited paper: Support-Vector Networks (1995) at Machine Learning (Cited By 5810)

Research Interest:

Support Vector Machines, Support Vector Method, Vector Machines, Extracting Support Data, Parallel Support

Show Temporal Interests (Do you want to see the change of his/her research interests?)

Education: [Edit]

Master University: Uzbek State University Master Major: Mathematics Master Date: 1958

Publications: [Edit disambiguation Result]

2009(1)
[49]Vladimir Vapnik, Akshay Vashist. A new learning paradigm: Learning using privileged information. Neural Networks, 2009: 544~557    Cited By 2[Bibtex]
2008(2)
[48]Ran El-Yaniv, Dmitry Pechyony, Vladimir Vapnik. Large Margin vs. Large Volume in Transductive Learning.  ECML/PKDD (1)'2008. pp.9~10    Cited By 3[Bibtex]
[47]Ran El-Yaniv, Dmitry Pechyony, Vladimir Vapnik. Large margin vs. large volume in transductive learning. Machine Learning, 2008: 173~188    Cited By 3[Bibtex]
2006(1)
[46]Jason Weston, Ronan Collobert, Fabian H. Sinz, Leon Bottou, Vladimir Vapnik. Inference with the Universum.  ICML'2006. pp.1009~1016    Cited By 30[Bibtex] [PDF]
2004(1)
[45]Hans Peter Graf, Eric Cosatto, Leon Bottou, Igor Durdanovic, Vladimir Vapnik. Parallel Support Vector Machines: The Cascade SVM.  NIPS'2004.     Cited By 107[Bibtex] [PDF]
2003(1)
[44]Jinbo Bi, Vladimir Vapnik. Learning with Rigorous Support Vector Machines.  COLT'2003. pp.243~257    Cited By 13[Bibtex] [PDF]
2002(4)
[43]Jason Weston, Olivier Chapelle, Andre Elisseeff, Bernhard Scholkopf, Vladimir Vapnik. Kernel Dependency Estimation.  NIPS'2002. pp.873~880    Cited By 77[Bibtex] [PDF]
[42]Isabelle Guyon, Jason Weston, Stephen Barnhill, Vladimir Vapnik. Gene Selection for Cancer Classification using Support Vector Machines. Machine Learning, 2002: 389~422    Cited By 1873[Bibtex]
[41]Olivier Chapelle, Vladimir Vapnik, Olivier Bousquet, Sayan Mukherjee. Choosing Multiple Parameters for Support Vector Machines. Machine Learning, 2002: 131~159    Cited By 972[Bibtex] [PDF]
[40]Olivier Chapelle, Vladimir Vapnik, Yoshua Bengio. Model Selection for Small Sample Regression. Machine Learning, 2002: 9~23    Cited By 33[Bibtex]
2001(1)
[39]Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladimir Vapnik. Support Vector Clustering. Journal of Machine Learning Research, 2001: 125~137    Cited By 557[Bibtex]
2000(5)
[38]Asa Ben-Hur, Hava T. Siegelmann, David Horn, Vladimir Vapnik. A Support Vector Clustering Method.  ICPR'2000. pp.2724~2727    Cited By 557[Bibtex] [PDF]
[37]Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso Poggio, Vladimir Vapnik. Feature Selection for SVMs.  NIPS'2000. pp.668~674    Cited By 474[Bibtex] [PDF]
[36]Olivier Chapelle, Jason Weston, Leon Bottou, Vladimir Vapnik. Vicinal Risk Minimization.  NIPS'2000. pp.416~422    Cited By 26[Bibtex]
[35]Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladimir Vapnik. A Support Vector Method for Clustering.  NIPS'2000. pp.367~373    Cited By 44[Bibtex] [PDF]
[34]Vladimir Vapnik, Olivier Chapelle. Bounds on Error Expectation for Support Vector Machines. Neural Computation, 2000: 2013~2036    Cited By 301[Bibtex]
1999(7)
[33]Vladimir Vapnik, Sayan Mukherjee. Support Vector Method for Multivariate Density Estimation.  NIPS'1999. pp.659~665    Cited By 66[Bibtex] [PDF]
[32]Olivier Chapelle, Vladimir Vapnik. Model Selection for Support Vector Machines.  NIPS'1999. pp.230~236    Cited By 198[Bibtex] [PDF]
[31]Olivier Chapelle, Vladimir Vapnik, Jason Weston. Transductive Inference for Estimating Values of Functions.  NIPS'1999. pp.421~427    Cited By 46[Bibtex] [PDF]
[30]Olivier Chapelle, Patrick Haffner, Vladimir Vapnik. Support vector machines for histogram-based image classification. IEEE Transactions on Neural Networks, 1999: 1055~1064   [Bibtex]
[29]Harris Drucker, Donghui Wu, Vladimir Vapnik. Support vector machines for spam categorization. IEEE Transactions on Neural Networks, 1999: 1048~1054    Cited By 649[Bibtex]
[28]Vladimir Cherkassky, Xuhui Shao, Filip Mulier, Vladimir Vapnik. Model complexity control for regression using VC generalization bounds. IEEE Transactions on Neural Networks, 1999: 1075~1089    Cited By 98[Bibtex]
[27]Vladimir Vapnik. An overview of statistical learning theory. IEEE Transactions on Neural Networks, 1999: 988~999    Cited By 1231[Bibtex]
1998(2)
[26]Alexander Gammerman, Katy S. Azoury, Vladimir Vapnik. Learning by Transduction.  UAI'1998. pp.148~155    Cited By 129[Bibtex] [PDF]
[25]Isabelle Guyon, John Makhoul, Richard M. Schwartz, Vladimir Vapnik. What Size Test Set Gives Good Error Rate Estimates?. IEEE Trans. Pattern Anal. Mach. Intell., 1998: 52~64    Cited By 78[Bibtex]
1997(3)
[24]Klaus-Robert Muller, Alex J. Smola, Gunnar Ratsch, Bernhard Scholkopf, Jens Kohlmorgen, Vladimir Vapnik. Predicting Time Series with Support Vector Machines.  ICANN'1997. pp.999~1004    Cited By 452[Bibtex] [PDF]
[23]Vladimir Vapnik. The Support Vector Method.  ICANN'1997. pp.263~271    Cited By 158[Bibtex] [PDF]
[22]Bernhard Scholkopf, Patrice Simard, Alex J. Smola, Vladimir Vapnik. Prior Knowledge in Support Vector Kernels.  NIPS'1997.     Cited By 187[Bibtex] [PDF]
1996(6)
[21]Isabelle Guyon, Nada Matic, Vladimir Vapnik. Discovering Informative Patterns and Data Cleaning.  Advances in Knowledge Discovery and Data Mining, 1996: 181~203    Cited By 172[Bibtex] [PDF]
[20]Bernhard Scholkopf, Chris Burges, Vladimir Vapnik. Incorporating Invariances in Support Vector Learning Machines.  ICANN'1996. pp.47~52    Cited By 165[Bibtex] [PDF]
[19]Volker Blanz, Bernhard Scholkopf, Heinrich H. Bulthoff, Chris Burges, Vladimir Vapnik, Thomas Vetter. Comparison of View-Based Object Recognition Algorithms Using Realistic 3D Models.  ICANN'1996. pp.251~256    Cited By 163[Bibtex] [PDF]
[18]Vladimir Vapnik. Statistical Theory of Generalization (Abstract).  ICML'1996. pp.557~557    Cited By 158[Bibtex] [PDF]
[17]Harris Drucker, Christopher J. C. Burges, Linda Kaufman, Alex J. Smola, Vladimir Vapnik. Support Vector Regression Machines.  NIPS'1996. pp.155~161    Cited By 483[Bibtex] [PDF]
[16]Vladimir Vapnik, Steven E. Golowich, Alex J. Smola. Support Vector Method for Function Approximation, Regression Estimation and Signal Processing.  NIPS'1996. pp.281~287    Cited By 822[Bibtex]
1995(3)
[15]Bernhard Scholkopf, Chris Burges, Vladimir Vapnik. Extracting Support Data for a Given Task.  KDD'1995. pp.252~257    Cited By 418[Bibtex] [PDF]
[14]Corinna Cortes, Harris Drucker, Dennis Hoover, Vladimir Vapnik. Capacity and Complexity Control in Predicting the Spread Between Borrowing and Lending Interest Rates.  KDD'1995. pp.51~56   [Bibtex] [PDF]
[13]Corinna Cortes, Vladimir Vapnik. Support-Vector Networks. Machine Learning, 1995: 273~297    Cited By 5810[Bibtex]
1994(4)
[12]Harris Drucker, Corinna Cortes, Lawrence D. Jackel, Yann LeCun, Vladimir Vapnik. Boosting and Other Machine Learning Algorithms.  ICML'1994. pp.53~61    Cited By 30[Bibtex] [PDF]
[11]Isabelle Guyon, Nada Matic, Vladimir Vapnik. Discovering Informative Patterns and Data Cleaning.  KDD Workshop'1994. pp.145~156    Cited By 172[Bibtex] [PDF]
[10]Vladimir Vapnik, Esther Levin, Yann LeCun. Measuring the VC-Dimension of a Learning Machine. Neural Computation, 1994: 851~876    Cited By 174[Bibtex] [PDF]
[9]Harris Drucker, Corinna Cortes, Lawrence D. Jackel, Yann LeCun, Vladimir Vapnik. Boosting and Other Ensemble Methods. Neural Computation, 1994: 1289~1301    Cited By 179[Bibtex]
1993(2)
[8]Corinna Cortes, Lawrence D. Jackel, Sara A. Solla, Vladimir Vapnik, John S. Denker. Learning Curves: Asymptotic Values and Rate of Convergence.  NIPS'1993. pp.327~334    Cited By 41[Bibtex]
[7]Vladimir Vapnik, Leon Bottou. Local Algorithms for Pattern Recognition and Dependencies Estimation. Neural Computation, 1993: 893~909    Cited By 53[Bibtex]
1992(3)
[6]Bernhard E. Boser, Isabelle Guyon, Vladimir Vapnik. A Training Algorithm for Optimal Margin Classifiers.  COLT'1992. pp.144~152    Cited By 3025[Bibtex]
[5]Isabelle Guyon, Bernhard E. Boser, Vladimir Vapnik. Automatic Capacity Tuning of Very Large VC-Dimension Classifiers.  NIPS'1992. pp.147~155    Cited By 100[Bibtex]
[4]Leon Bottou, Vladimir Vapnik. Local Learning Algorithms. Neural Computation, 1992: 888~900    Cited By 304[Bibtex]
1991(2)
[3]Vladimir Vapnik. Principles of Risk Minimization for Learning Theory.  NIPS'1991. pp.831~838    Cited By 158[Bibtex]
[2]Isabelle Guyon, Vladimir Vapnik, Bernhard E. Boser, Leon Bottou, Sara A. Solla. Structural Risk Minimization for Character Recognition.  NIPS'1991. pp.471~479    Cited By 86[Bibtex]
1989(1)
[1]Vladimir Vapnik. Inductive Principles of the Search for Empirical Dependences (Methods Based on Weak Convergence of Probability Measures).  COLT'1989. pp.3~21    Cited By 158[Bibtex]