dblp.uni-trier.dewww.uni-trier.de

Vladimir Vapnik Vis

List of publications from the DBLP Bibliography Server - FAQ
Coauthor Index - Ask others: ACM DL/Guide - CiteSeerX - CSB - MetaPress - Google - Bing - Yahoo

*2009
48EEVladimir Vapnik, Akshay Vashist: A new learning paradigm: Learning using privileged information. Neural Networks 22(5-6): 544-557 (2009)
2008
47EERan El-Yaniv, Dmitry Pechyony, Vladimir Vapnik: Large Margin vs. Large Volume in Transductive Learning. ECML/PKDD (1) 2008: 9-10
46EERan El-Yaniv, Dmitry Pechyony, Vladimir Vapnik: Large margin vs. large volume in transductive learning. Machine Learning 72(3): 173-188 (2008)
2006
45EEJason Weston, Ronan Collobert, Fabian H. Sinz, Léon Bottou, Vladimir Vapnik: Inference with the Universum. ICML 2006: 1009-1016
2004
44EEHans Peter Graf, Eric Cosatto, Léon Bottou, Igor Durdanovic, Vladimir Vapnik: Parallel Support Vector Machines: The Cascade SVM. NIPS 2004
2003
43EEJinbo Bi, Vladimir Vapnik: Learning with Rigorous Support Vector Machines. COLT 2003: 243-257
2002
42EEJason Weston, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf, Vladimir Vapnik: Kernel Dependency Estimation. NIPS 2002: 873-880
41 Olivier Chapelle, Vladimir Vapnik, Olivier Bousquet, Sayan Mukherjee: Choosing Multiple Parameters for Support Vector Machines. Machine Learning 46(1-3): 131-159 (2002)
40 Isabelle Guyon, Jason Weston, Stephen Barnhill, Vladimir Vapnik: Gene Selection for Cancer Classification using Support Vector Machines. Machine Learning 46(1-3): 389-422 (2002)
39 Olivier Chapelle, Vladimir Vapnik, Yoshua Bengio: Model Selection for Small Sample Regression. Machine Learning 48(1-3): 9-23 (2002)
2001
38EEAsa Ben-Hur, David Horn, Hava T. Siegelmann, Vladimir Vapnik: Support Vector Clustering. Journal of Machine Learning Research 2: 125-137 (2001)
2000
37EEAsa Ben-Hur, Hava T. Siegelmann, David Horn, Vladimir Vapnik: A Support Vector Clustering Method. ICPR 2000: 2724-2727
36 Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladimir Vapnik: A Support Vector Method for Clustering. NIPS 2000: 367-373
35 Olivier Chapelle, Jason Weston, Léon Bottou, Vladimir Vapnik: Vicinal Risk Minimization. NIPS 2000: 416-422
34 Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso Poggio, Vladimir Vapnik: Feature Selection for SVMs. NIPS 2000: 668-674
33 Vladimir Vapnik, Olivier Chapelle: Bounds on Error Expectation for Support Vector Machines. Neural Computation 12(9): 2013-2036 (2000)
1999
32EEOlivier Chapelle, Vladimir Vapnik: Model Selection for Support Vector Machines. NIPS 1999: 230-236
31EEOlivier Chapelle, Vladimir Vapnik, Jason Weston: Transductive Inference for Estimating Values of Functions. NIPS 1999: 421-427
30EEVladimir Vapnik, Sayan Mukherjee: Support Vector Method for Multivariate Density Estimation. NIPS 1999: 659-665
29EEHarris Drucker, Donghui Wu, Vladimir Vapnik: Support vector machines for spam categorization. IEEE Transactions on Neural Networks 10(5): 1048-1054 (1999)
28EEOlivier Chapelle, Patrick Haffner, Vladimir Vapnik: Support vector machines for histogram-based image classification. IEEE Transactions on Neural Networks 10(5): 1055-1064 (1999)
27EEVladimir Cherkassky, Xuhui Shao, Filip Mulier, Vladimir Vapnik: Model complexity control for regression using VC generalization bounds. IEEE Transactions on Neural Networks 10(5): 1075-1089 (1999)
26EEVladimir Vapnik: An overview of statistical learning theory. IEEE Transactions on Neural Networks 10(5): 988-999 (1999)
1998
25EEAlexander Gammerman, Katy S. Azoury, Vladimir Vapnik: Learning by Transduction. UAI 1998: 148-155
24EEIsabelle Guyon, John Makhoul, Richard M. Schwartz, Vladimir Vapnik: What Size Test Set Gives Good Error Rate Estimates?. IEEE Trans. Pattern Anal. Mach. Intell. 20(1): 52-64 (1998)
1997
23 Vladimir Vapnik: The Support Vector Method. ICANN 1997: 263-271
22 Klaus-Robert Müller, Alex J. Smola, Gunnar Rätsch, Bernhard Schölkopf, Jens Kohlmorgen, Vladimir Vapnik: Predicting Time Series with Support Vector Machines. ICANN 1997: 999-1004
21 Bernhard Schölkopf, Patrice Simard, Alex J. Smola, Vladimir Vapnik: Prior Knowledge in Support Vector Kernels. NIPS 1997
1996
20 Volker Blanz, Bernhard Schölkopf, Heinrich H. Bülthoff, Chris Burges, Vladimir Vapnik, Thomas Vetter: Comparison of View-Based Object Recognition Algorithms Using Realistic 3D Models. ICANN 1996: 251-256
19 Bernhard Schölkopf, Chris Burges, Vladimir Vapnik: Incorporating Invariances in Support Vector Learning Machines. ICANN 1996: 47-52
18 Vladimir Vapnik: Statistical Theory of Generalization (Abstract). ICML 1996: 557
17EEHarris Drucker, Christopher J. C. Burges, Linda Kaufman, Alex J. Smola, Vladimir Vapnik: Support Vector Regression Machines. NIPS 1996: 155-161
16EEVladimir Vapnik, Steven E. Golowich, Alex J. Smola: Support Vector Method for Function Approximation, Regression Estimation and Signal Processing. NIPS 1996: 281-287
15 Isabelle Guyon, Nada Matic, Vladimir Vapnik: Discovering Informative Patterns and Data Cleaning. Advances in Knowledge Discovery and Data Mining 1996: 181-203
1995
14 Bernhard Schölkopf, Chris Burges, Vladimir Vapnik: Extracting Support Data for a Given Task. KDD 1995: 252-257
13 Corinna Cortes, Harris Drucker, Dennis Hoover, Vladimir Vapnik: Capacity and Complexity Control in Predicting the Spread Between Borrowing and Lending Interest Rates. KDD 1995: 51-56
12 Corinna Cortes, Vladimir Vapnik: Support-Vector Networks. Machine Learning 20(3): 273-297 (1995)
1994
11 Harris Drucker, Corinna Cortes, Lawrence D. Jackel, Yann LeCun, Vladimir Vapnik: Boosting and Other Machine Learning Algorithms. ICML 1994: 53-61
10 Isabelle Guyon, Nada Matic, Vladimir Vapnik: Discovering Informative Patterns and Data Cleaning. KDD Workshop 1994: 145-156
9EEVladimir Vapnik, Esther Levin, Yann LeCun: Measuring the VC-Dimension of a Learning Machine. Neural Computation 6(5): 851-876 (1994)
8EEHarris Drucker, Corinna Cortes, Lawrence D. Jackel, Yann LeCun, Vladimir Vapnik: Boosting and Other Ensemble Methods. Neural Computation 6(6): 1289-1301 (1994)
1993
7EECorinna Cortes, Lawrence D. Jackel, Sara A. Solla, Vladimir Vapnik, John S. Denker: Learning Curves: Asymptotic Values and Rate of Convergence. NIPS 1993: 327-334
6EEVladimir Vapnik, Léon Bottou: Local Algorithms for Pattern Recognition and Dependencies Estimation. Neural Computation 5(6): 893-909 (1993)
1992
5EEBernhard E. Boser, Isabelle Guyon, Vladimir Vapnik: A Training Algorithm for Optimal Margin Classifiers. COLT 1992: 144-152
4EEIsabelle Guyon, Bernhard E. Boser, Vladimir Vapnik: Automatic Capacity Tuning of Very Large VC-Dimension Classifiers. NIPS 1992: 147-155
1991
3EEIsabelle Guyon, Vladimir Vapnik, Bernhard E. Boser, Léon Bottou, Sara A. Solla: Structural Risk Minimization for Character Recognition. NIPS 1991: 471-479
2EEVladimir Vapnik: Principles of Risk Minimization for Learning Theory. NIPS 1991: 831-838
1989
1EEVladimir Vapnik: Inductive Principles of the Search for Empirical Dependences (Methods Based on Weak Convergence of Probability Measures). COLT 1989: 3-21

Coauthor Index

1Katy S. Azoury [25]
2Stephen Barnhill [40]
3Asa Ben-Hur [36] [37] [38]
4Yoshua Bengio [39]
5Jinbo Bi [43]
6Volker Blanz [20]
7Bernhard E. Boser [3] [4] [5]
8Léon Bottou [3] [6] [35] [44] [45]
9Olivier Bousquet [41]
10Heinrich H. Bülthoff [20]
11Christopher J. C. Burges (Chris Burges) [14] [17] [19] [20]
12Olivier Chapelle [28] [31] [32] [33] [34] [35] [39] [41] [42]
13Vladimir Cherkassky [27]
14Ronan Collobert [45]
15Corinna Cortes [7] [8] [11] [12] [13]
16Eric Cosatto [44]
17John S. Denker [7]
18Harris Drucker [8] [11] [13] [17] [29]
19Igor Durdanovic [44]
20Ran El-Yaniv [46] [47]
21André Elisseeff [42]
22Alexander Gammerman (Alex J. Gammerman) [25]
23Steven E. Golowich [16]
24Hans Peter Graf [44]
25Isabelle Guyon [3] [4] [5] [10] [15] [24] [40]
26Patrick Haffner [28]
27Dennis Hoover [13]
28David Horn [36] [37] [38]
29Lawrence D. Jackel [7] [8] [11]
30Linda Kaufman [17]
31Jens Kohlmorgen [22]
32Yann LeCun [8] [9] [11]
33Esther Levin [9]
34John Makhoul [24]
35Nada Matic [10] [15]
36Sayan Mukherjee [30] [34] [41]
37Filip Mulier [27]
38Klaus-Robert Müller [22]
39Dmitry Pechyony [46] [47]
40Tomaso Poggio [34]
41Massimiliano Pontil [34]
42Gunnar Rätsch [22]
43Bernhard Schölkopf [14] [19] [20] [21] [22] [42]
44Richard M. Schwartz [24]
45Xuhui Shao [27]
46Hava T. Siegelmann [36] [37] [38]
47Patrice Y. Simard (Patrice Simard) [21]
48Fabian H. Sinz [45]
49Alexander J. Smola (Alex J. Smola) [16] [17] [21] [22]
50Sara A. Solla [3] [7]
51Akshay Vashist [48]
52Thomas Vetter [20]
53Jason Weston [31] [34] [35] [40] [42] [45]
54Donghui Wu [29]

Colors in the list of coauthors

Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)