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Prof. Dr. Vladimir Vapnik

Raum Nummer: 212
Fax: 07071-601-552

 

Bild von Vapnik, Vladimir, Prof. Dr.

Vladimir Vapnik

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Artikel (6):

Corfield D, Schölkopf B und Vapnik V (Juli-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 und Mukherjee S (2002) Choosing Multiple Parameters for Support Vector Machines Machine Learning 46(1) 131-159.
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Chapelle O, Vapnik V und Bengio Y (2002) Model Selection for Small Sample Regression Machine Learning 48(1-3) 9-23.
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Vapnik V und Chapelle O (2000) Bounds on Error Expectation for Support Vector Machines Neural Computation 12(9) 2013-2036.
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Chapelle O, Haffner P und Vapnik V (1999) SVMs for Histogram Based Image Classification IEEE Transactions on Neural Networks (9).
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Schölkopf B, Sung K, Burges C, Girosi F, Niyogi P, Poggio T und 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.

Beiträge zu Tagungsbänden (13):

Weston J, Collobert R, Sinz F, Bottou L und Vapnik V (Juni-2006) Inference with the Universum, 23rd International Conference on Machine Learning (ICML 2006), ACM Press, New York, NY, USA, 1009-1016.
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Weston J, Chapelle O, Elisseeff A, Schölkopf B und Vapnik V (Oktober-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.
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Weston J, Mukherjee S, Chapelle O, Pontil M, Poggio T und 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.
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Chapelle O, Weston J, Bottou L und 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.
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Chapelle O und Vapnik V (Juni-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.
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Chapelle O, Vapnik V und Weston J (Juni-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.
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Müller K-R, Smola AJ, Rätsch G, Schölkopf B, Kohlmorgen J und 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 und Vapnik V (Juni-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.
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Schölkopf B, Smola AJ, Müller K-R, Burges C und Vapnik V (Februar-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 und Vapnik V (Oktober-1997) Predicting time series with support vector 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.
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Blanz V, Schölkopf B, Bülthoff HH, Burges C, Vapnik V und Vetter T (Juli-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.
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Schölkopf B, Burges C und Vapnik V (Juli-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 und 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.

Technische Berichte (3):

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

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Last updated: Montag, 22.05.2017