Vladimir Vapnik

According to our database1, Vladimir Vapnik authored at least 72 papers between 1989 and 2017.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

Homepages:

On csauthors.net:

Bibliography

2017
Knowledge transfer in SVM and neural networks.
Ann. Math. Artif. Intell., 2017

2016
Synergy of Monotonic Rules.
Journal of Machine Learning Research, 2016

Learning with Intelligent Teacher.
Proceedings of the Conformal and Probabilistic Prediction with Applications, 2016

2015
Constructive setting for problems of density ratio estimation.
Statistical Analysis and Data Mining, 2015

Learning using privileged information: similarity control and knowledge transfer.
Journal of Machine Learning Research, 2015

V-matrix method of solving statistical inference problems.
Journal of Machine Learning Research, 2015

Unifying distillation and privileged information.
CoRR, 2015

Statistical Inference Problems and Their Rigorous Solutions - In memory of Alexey Chervonenkis.
Proceedings of the Statistical Learning and Data Sciences - Third International Symposium, 2015

Learning with Intelligent Teacher: Similarity Control and Knowledge Transfer - In memory of Alexey Chervonenkis.
Proceedings of the Statistical Learning and Data Sciences - Third International Symposium, 2015

2014
A Constructive Setting for the Problem of Density Ratio Estimation.
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

2013
Learning by Transduction
CoRR, 2013

Multidimensional splines with infinite number of knots as SVM kernels.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

On the Uniform Convergence of the Frequencies of Occurrence of Events to Their Probabilities.
Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

2011
Machine learning classification with confidence: Application of transductive conformal predictors to MRI-based diagnostic and prognostic markers in depression.
NeuroImage, 2011

2010
On the Theory of Learnining with Privileged Information.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

SMO-Style Algorithms for Learning Using Privileged Information.
Proceedings of The 2010 International Conference on Data Mining, 2010

2009
A new learning paradigm: Learning using privileged information.
Neural Networks, 2009

Learning using hidden information (Learning with teacher).
Proceedings of the International Joint Conference on Neural Networks, 2009

2008
Large margin vs. large volume in transductive learning.
Machine Learning, 2008

Large Margin vs. Large Volume in Transductive Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

2006
Inference with the Universum.
Proceedings of the Machine Learning, 2006

Learning hidden information: SVM+.
Proceedings of the 2006 IEEE International Conference on Granular Computing, 2006

2004
Parallel Support Vector Machines: The Cascade SVM.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2003
Learning with Rigorous Support Vector Machines.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

2002
Gene Selection for Cancer Classification using Support Vector Machines.
Machine Learning, 2002

Choosing Multiple Parameters for Support Vector Machines.
Machine Learning, 2002

Model Selection for Small Sample Regression.
Machine Learning, 2002

Kernel Dependency Estimation.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2001
Support Vector Clustering.
Journal of Machine Learning Research, 2001

2000
Bounds on Error Expectation for Support Vector Machines.
Neural Computation, 2000

Feature Selection for SVMs.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Vicinal Risk Minimization.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

A Support Vector Method for Clustering.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

A Support Vector Clustering Method.
Proceedings of the 15th International Conference on Pattern Recognition, 2000

1999
An overview of statistical learning theory.
IEEE Trans. Neural Networks, 1999

Support vector machines for spam categorization.
IEEE Trans. Neural Networks, 1999

Model complexity control for regression using VC generalization bounds.
IEEE Trans. Neural Networks, 1999

Support vector machines for histogram-based image classification.
IEEE Trans. Neural Networks, 1999

Support Vector Method for Multivariate Density Estimation.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Transductive Inference for Estimating Values of Functions.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Model Selection for Support Vector Machines.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

1998
What Size Test Set Gives Good Error Rate Estimates?.
IEEE Trans. Pattern Anal. Mach. Intell., 1998

Learning by Transduction.
Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

Statistical learning theory.
Wiley, ISBN: 978-0-471-03003-4, 1998

1997
Comparing support vector machines with Gaussian kernels to radial basis function classifiers.
IEEE Trans. Signal Processing, 1997

Prior Knowledge in Support Vector Kernels.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

The Support Vector Method.
Proceedings of the Artificial Neural Networks, 1997

Predicting Time Series with Support Vector Machines.
Proceedings of the Artificial Neural Networks, 1997

1996
Support Vector Method for Function Approximation, Regression Estimation and Signal Processing.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Support Vector Regression Machines.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Statistical Theory of Generalization (Abstract).
Proceedings of the Machine Learning, 1996

Incorporating Invariances in Support Vector Learning Machines.
Proceedings of the Artificial Neural Networks, 1996

Comparison of View-Based Object Recognition Algorithms Using Realistic 3D Models.
Proceedings of the Artificial Neural Networks, 1996

Discovering Informative Patterns and Data Cleaning.
Advances in Knowledge Discovery and Data Mining, 1996

1995
Support-Vector Networks.
Machine Learning, 1995

Extracting Support Data for a Given Task.
Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), 1995

Capacity and Complexity Control in Predicting the Spread Between Borrowing and Lending Interest Rates.
Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), 1995

Estimation of dependencies based on small number of observations.
Proceedings of the IEEE/IAFE 1995 Computational Intelligence for Financial Engineering, 1995

1994
Measuring the VC-Dimension of a Learning Machine.
Neural Computation, 1994

Boosting and Other Ensemble Methods.
Neural Computation, 1994

Discovering Informative Patterns and Data Cleaning.
Proceedings of the Knowledge Discovery in Databases: Papers from the 1994 AAAI Workshop, 1994

Comparison of classifier methods: a case study in handwritten digit recognition.
Proceedings of the 12th IAPR International Conference on Pattern Recognition, 1994

Boosting and Other Machine Learning Algorithms.
Proceedings of the Machine Learning, 1994

1993
Local Algorithms for Pattern Recognition and Dependencies Estimation.
Neural Computation, 1993

Learning Curves: Asymptotic Values and Rate of Convergence.
Proceedings of the Advances in Neural Information Processing Systems 6, 1993

Writer-adaptation for on-line handwritten character recognition.
Proceedings of the 2nd International Conference Document Analysis and Recognition, 1993

1992
Local Learning Algorithms.
Neural Computation, 1992

Automatic Capacity Tuning of Very Large VC-Dimension Classifiers.
Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

A Training Algorithm for Optimal Margin Classifiers.
Proceedings of the Fifth Annual ACM Conference on Computational Learning Theory, 1992

1991
Principles of Risk Minimization for Learning Theory.
Proceedings of the Advances in Neural Information Processing Systems 4, 1991

Structural Risk Minimization for Character Recognition.
Proceedings of the Advances in Neural Information Processing Systems 4, 1991

1989
Inductive Principles of the Search for Empirical Dependences (Methods Based on Weak Convergence of Probability Measures).
Proceedings of the Second Annual Workshop on Computational Learning Theory, 1989


  Loading...