Contact

Prof. Dr. Vladimir Vapnik

Room number: 212
Fax: +49-7071-601-552

 

Picture of Vapnik, Vladimir, Prof. Dr.

Vladimir Vapnik

  Unit: 

Preferences: 
References per page: Year: Medium:

  
Show abstracts

Articles (6):

Corfield D, Schölkopf B and Vapnik V (July-2009) Falsificationism and Statistical Learning Theory: Comparing the Popper and Vapnik-Chervonenkis Dimensions Journal for General Philosophy of Science 40(1) 51-58.
Chapelle O, Vapnik V, Bousquet O and Mukherjee S (2002) Choosing Multiple Parameters for Support Vector Machines Machine Learning 46(1) 131-159.
pdfps
Chapelle O, Vapnik V and Bengio Y (2002) Model Selection for Small Sample Regression Machine Learning 48(1-3) 9-23.
ps
Vapnik V and Chapelle O (2000) Bounds on Error Expectation for Support Vector Machines Neural Computation 12(9) 2013-2036.
default
Chapelle O, Haffner P and Vapnik V (1999) SVMs for Histogram Based Image Classification IEEE Transactions on Neural Networks (9).
default
Schölkopf B, Sung K, Burges C, Girosi F, Niyogi P, Poggio T and Vapnik V (November-1997) Comparing support vector machines with Gaussian kernels to radial basis function classifiers IEEE Transactions on Signal Processing 45(11) 2758-2765.

Conference papers (13):

Weston J, Collobert R, Sinz F, Bottou L and Vapnik V (June-2006) Inference with the Universum, 23rd International Conference on Machine Learning (ICML 2006), ACM Press, New York, NY, USA, 1009-1016.
pdf
Weston J, Chapelle O, Elisseeff A, Schölkopf B and Vapnik V (October-2003) Kernel Dependency Estimation In: Advances in Neural Information Processing Systems 15, , Sixteenth Annual Conference on Neural Information Processing Systems (NIPS 2002), MIT Press, Cambridge, MA, USA, 873-880.
pdf
Weston J, Mukherjee S, Chapelle O, Pontil M, Poggio T and Vapnik V (April-2001) Feature Selection for SVMs In: Advances in Neural Information Processing Systems 13, , Fourteenth Annual Neural Information Processing Systems Conference (NIPS 2000), MIT Press, Cambridge, MA, USA, 668-674.
pdf
Chapelle O, Weston J, Bottou L and Vapnik V (April-2001) Vicinal Risk Minimization In: Advances in Neural Information Processing Systems 13, , Fourteenth Annual Neural Information Processing Systems Conference (NIPS 2000), MIT Press, Cambridge, MA, USA, 416-422.
pdf
Chapelle O and Vapnik V (June-2000) Model Selection for Support Vector Machines In: Advances in Neural Information Processing Systems 12, , Thirteenth Annual Neural Information Processing Systems Conference (NIPS 1999), MIT Press, Cambridge, MA, USA, 230-236.
pdf
Chapelle O, Vapnik V and Weston J (June-2000) Transductive Inference for Estimating Values of Functions In: Advances in Neural Information Processing Systems 12, , Thirteenth Annual Neural Information Processing Systems Conference (NIPS 1999), MIT Press, Cambridge, MA, USA, 421-427.
pdf
Müller K-R, Smola AJ, Rätsch G, Schölkopf B, Kohlmorgen J and Vapnik V (1999) Using support vector machines for time series prediction In: Advances in kernel methods: support vector learning, , Eleventh Annual Conference on Neural Information Processing (NIPS 1997), MIT Press, Cambridge, MA, USA, 243-253.
Schölkopf B, Simard P, Smola AJ and Vapnik V (June-1998) Prior knowledge in support vector kernels In: Advances in Neural Information Processing Systems 10, , Eleventh Annual Conference on Neural Information Processing (NIPS 1997), MIT Press, Cambridge, MA, USA, 640-646, Series: A Bradford Book.
pdf
Schölkopf B, Smola AJ, Müller K-R, Burges C and Vapnik V (February-1998) Support Vector methods in learning and feature extraction, Ninth Australian Conference on Neural Networks (ACNN'98), University of Queensland, Brisbane, Australia, 72-78.
Müller K-R, Smola AJ, Rätsch G, Schölkopf B, Kohlmorgen J and Vapnik V (October-1997) Predicting time series with support vectur machines In: Artificial Neural Networks - ICANN '97, , 7th International Conference on Artificial Neural Networks, Springer, Berlin, Germany, 999-1004, Series: Lecture Notes in Computer Science ; 1327.
pdf
Blanz V, Schölkopf B, Bülthoff HH, Burges C, Vapnik V and Vetter T (July-1996) Comparison of view-based object recognition algorithms using realistic 3D models In: Artificial Neural Networks - ICANN 96, , 6th International Conference on Artificial Neural Networks, Springer, Berlin, Germany, 251-256, Series: Lecture Notes in Computer Science ; 1112.
pdf
Schölkopf B, Burges C and Vapnik V (July-1996) Incorporating invariances in support vector learning machines In: Artificial Neural Networks - ICANN 96, , 6th International Conference on Artificial Neural Networks, Springer, Berlin, Germany, 47-52, Series: Lecture Notes in Computer Science ; 1112.
Schölkopf B, Burges C and Vapnik V (August-1995) Extracting support data for a given task, First International Conference on Knowledge Discovery & Data Mining (KDD-95), AAAI Press, Menlo Park, CA, USA, 252-257.

Technical reports (3):

Corfield D, Schölkopf B and Vapnik V: Popper, Falsification and the VC-dimension, 145, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (November-2005).
pdf
Weston J, Chapelle O, Elisseeff A, Schölkopf B and Vapnik V: Kernel Dependency Estimation, 98, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (August-2002).
pdf
Vapnik V, Burges CJC and Schölkopf B: A New Method for Constructing Artificial Neural Networks, AT & T Bell Laboratories, (1995).

Export as:
BibTeX, XML, Pubman, Edoc, RTF
Last updated: Tuesday, 18.11.2014