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A tutorial on support vector machines for pattern recognition (1997)

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by Christopher J. C. Burges
Citations:1656 - 11 self
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BibTeX

@MISC{Burges97atutorial,
    author = {Christopher J. C. Burges},
    title = {A tutorial on support vector machines for pattern recognition},
    year = {1997}
}

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Abstract

Citations

6695 Statistical Learning Theory - Vapnik - 1998
3912 CM: Neural Networks for Pattern Recognition - Bishop - 1995
3200 Topics in Matrix Analysis - Horn, Johnson - 1994
1493 Vapnik V: Support-Vector Networks - Cortes - 1995
1471 Numerical Recipes in C: The Art of Scientific Computing - Press, Flannery, et al. - 1992
1366 Text categorization with support vector machines: learning with many relevant features - Joachims - 1998
935 A training algorithm for optimal margin classifiers - Boser, Guyon, et al. - 1992
882 Practical Methods of Optimization - Fletcher - 1987
801 A probabilistic theory of pattern recognition - Devroye, Györfi, et al. - 1996
454 Training support vector machines: an application to face detection - Osuna, Freund, et al. - 1997
261 Introduction to Applied Mathematics - Strang - 1986
221 Structural risk minimization over data-dependent hierarchies - Shawe-Taylor, Bartlett, et al. - 1940
208 Rozonoer L: Theoretical foundations of the potential function method in pattern recognition learning. Automat Rem Contr - Aizerman, Braverman - 1964
203 Girosi F: An improved training algorithm for support vector machines - Osuna, Freund - 1997
186 Numerical Recipes in C: The Art of Scientific Computing (Cambridge - Press, Teukolsky, et al. - 1992
168 An Equivalence Between Sparse Approximation and Support Vector Machines. Neural Comput - Girosi - 1998
155 Nonlinear programming - Mangasarian - 1969
154 Extracting support data for a given task - Scholkopf, Burges, et al. - 1995
140 Support vector method for function approximation, regression estimation, and signal processing - Vapnik, Golowich, et al. - 1997
130 LOQO: An interior point code for quadratic programming - Vanderbei - 1994
122 Support Vector Machines, Reproducing Kernel Hilbert Spaces and the randomized GACV - Wahba - 1997
122 Improving the accuracy and speed of support vector learning machines - Burges, Schölkopf - 1997
120 Simplified support vector decision rules - Burges - 1996
120 Introductory Real Analysis - Kolmogorov, Fomin - 1970
119 The connection between regularization operators and support vector kernels. Neural Networks - Smola, Schölkopf, et al. - 1998
105 Support Vector Learning - Schőlkopf - 1997
98 Support vector regression machines - Drucker, Burges, et al. - 1997
97 Comparing Support Vector Machines With Gaussian Kernels to Radial Basis Function Classifiers - Scholkopf, Sung, et al. - 1997
96 Predicting time series with support vector machines - Muller, Smola, et al. - 1997
93 Some stable methods for calculating inertia and solving symmetric linear systems - Bunch, Kaufman - 1977
91 Introduction to Linear Regression Analysis - Montgomery, Peck, et al. - 2001
79 Prior knowledge in support vector kernels - Schölkopf, Simard, et al. - 1998
67 On a kernel-based method for pattern recognition, regression, approximation and operator inversion - Smola, Scholkopf - 1998
66 A Hilbert space problem book - Halmos - 1967
63 Nonlinear prediction of chaotic time series using support vector machines - Mukherjee, Osuna, et al. - 1997
61 V.: Incorporating invariances in support vector learning machines - Schlkopf, Burges, et al. - 1996
52 On the solution of large quadratic programming problems with bound constraints - Moré, Toraldo - 1991
42 Estimation of Dependences Based on Empirical Data [in Russian - Vapnik - 1979
39 Reducing the run-time complexity in support vector machines. Advances in kernel methods: support vector learning - Osuna, Girosi - 1999
38 Nonlinear Programming: Theory, Algorithms and Applications - McCormick - 1983
33 General cost functions for support vector regression - Smola, Schölkopf, et al. - 1998
32 Structural risk minimization for character recognition', this volume - Guyon, Vapnik, et al. - 1992
28 at al. Numerical recipes in C: the art of scienti c computing Cambridge - Press - 1988
24 A framework for structural risk minimization - Shawe-Taylor, Bartlett, et al. - 1996
22 László Györfi, and Gábor Lugosi. A Probabilistic Approach to Pattern Recognition - Devroye - 1996
21 Neural networks and the bias / variance dilemma. Neural Computation - Geman, Bienstock, et al. - 1992
18 Geometry in learning - Bennett, Bredensteiner - 1998
18 Comparing support vector machines with gaussian kernels to radial basis function classifiers - Schoelkopf, Sung, et al. - 1996
16 On the solution of large quadratic programming problems with bound constraints - JJ, Toraldo - 1991
16 Identifying speaker with support vector networks - Schmidt - 1996
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