vapnik, vladimir

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Results for vapnik, vladimir

1. An overview of statistical learning theory - Neural Networks, IEEE

IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 10, NO. 5, SEPTEMBER
1999. An Overview of Statistical Learning Theory. Vladimir N. Vapnik. Abstract—
Statistical learning theory was introduced in the late. 1960's. Until the 1990's it

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2. SUPPORT-VECTOR NETWORKS Corinna Cortes 1 and Vladimir

Corinna Cortes 1 and Vladimir Vapnik 2. AT&T Labs-Research, USA. Abstract.
The support-vector network is a new learning machine for two-group
classification problems. The machine conceptually implements the following idea
: input vect
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3. Statistical Learning Theory——Vapnik.djvu - Read

addressed to the permissions Department, John Wiley & Sons, Inc., 60S Third
Avenue, New York,. NY 10158---0012, (212) 850---6011, fax (212) 850---6008, E-
Mail: [email protected] Library ofCongress Cataloging-in-Publication
Data: Vapnik<
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4. Support-Vector Networks - Springer Link

VLADIMIR VAPNIK [email protected] AT&T Bell Labs., Holmdel, NJ 07733,
USA. Editor: Lorenza Saitta. Abstract. The support-vector network is a new
learning machine for two-group classification problems. The machine
conceptually impl
Tags:vapnik, vladimir

5. Local Learning Algorithms L щeon Bottou, Vladimir Vapnik AT&T

L щeon Bottou, Vladimir Vapnik. AT&T Bell Laboratories, Holmdel, NJ 07733,
USA. Abstract. Very rarely are training data evenly distributed in the input space.
Local learning algo- rithms attempt to locally adjust the capacity of the train
Tags:vapnik, vladimir

6. Similarity Control and Knowledge Transfer - Journal of Machine

Learning Using Privileged Information: Similarity Control and Knowledge
Transfer. Vladimir Vapnik vladimir.vapnik@gmail.com. Columbia University. New
York, NY 10027, USA. Facebook AI Research. New York, NY 10017, USA. Rauf
Izm
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7. Statistical Learning Theory by Vladimir N. Vapnik - Semantic Scholar

Vladimir N. Vapnik. Statistical Learning Based On The Vc Class. A
comprehensive look at learning and generalization theory. The statistical theory
of learning and generalization concerns the problem of choosing desired
functio
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8. The Nature of Statistical Learning Theory - Andrew.cmu.edu

Combinatorial Optimization, Monte Carlo Simulation, and Machine Learning,.
Studenſ: Probabilistic Conditional Independence Structures. Vapnik: The Nature
of Statistical Learning Theory, Second Edition,. Wallace: Statistical and Inductive
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9. BRUTE FORCE AND INTELLIGENT METHODS OF LEARNING

1. BRUTE FORCE AND INTELLIGENT METHODS. OF LEARNING. Vladimir
Vapnik. Columbia University, New York. Facebook AI Research, New York. Page
2. 2. PART 1. BASIC LINE OF REASONING. Problem of pattern recognition can
be formulated
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10. Measuring the VC-dimension of a Learning Machine Vladimir

Vladimir Vapnik, Esther Levin, Yann Le Cun. AT&T Bell Laboratories. 101
Crawfords Corner Road, Holmdel, NJ 07733. Abstract. A method for measuring
the capacity of learning machines is described. The method is based on fitting a
theor
Tags:vapnik, vladimir

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