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https://alex.smola.org/papers/2000/SchSmoWilBar00.pdf
New Support Vector Algorithms 1209 Figure 1: In SV regression, a desired accuracy "is specified a priori. It is then attempted to fit a tube with radius "to the data. The trade-off between model complexity and points lying outside the tube (with positive slack variables »)is determined by minimizing the expression 1.5.
http://www.stat.purdue.edu/~yuzhu/stat598m3/Papers/NewSVM.pdf
New Support Vector Algorithms Bernhard Scholkopf¨ ¤ Alex J. Smola GMD FIRST, 12489 Berlin, Germany, and Department of Engineering, Australian National University, Canberra 0200, Australia Robert C. Williamson DepartmentofEngineering,AustralianNationalUniversity,Canberra 0200,Australia Peter L. Bartlett
https://www.semanticscholar.org/paper/New-Support-Vector-Algorithms-Sch%C3%B6lkopf-Smola/8d73c0d0c92446102fdb6cc728b5d69674a1a387
We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter lets one effectively control the number of support vectors. While this can be useful in its own right, the parameterization has the additional benefit of enabling us to eliminate one of the other free parameters of the algorithm: the accuracy parameter in the …
https://papers.nips.cc/paper/1563-shrinking-the-tube-a-new-support-vector-regression-algorithm.pdf
Shrinking the Tube: A New Support Vector Regression Algorithm 331 2 ZJ-SV REGRESSION AND c-SV REGRESSION To estimate functions (1) from empirical data (2) we proceed as follows (SchOlkopf et aI.,
https://www.deepdyve.com/lp/mit-press/new-support-vector-algorithms-4I2gUjGvJh
May 01, 2000 · New Support Vector Algorithms In these algorithms, a parameter ν lets one effectively control the number of support vectors. While this can be useful in its own right, the parameterization has the additional benefit of enabling us to eliminate one of the other free parameters of the algorithm: the accuracy parameter ϵ in the regression case, and the …
http://www.kernel-machines.org/publications/SchSmoWilBar98
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https://www.mitpressjournals.org/doi/10.1162/089976600300015565
Mar 13, 2006 · We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter ν lets one effectively control the number of support vectors. ... Alex J. Smola . GMD FIRST, 12489 Berlin, Germany, and Department of Engineering, Australian National University, Canberra 0200, Australia. Robert C. Williamson .Cited by: 3121
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.94.2928
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter º lets one effectively control the number of support vectors. While this can be useful in its own right, the parameterization has the additional benefit of enabling us to eliminate one of …
https://www.sciencedirect.com/science/article/pii/S0893608009002019
Like the previous v -SVM, the proposed support vector algorithms have the advantage of using the parameter 0 ≤ v ≤ 1 for controlling the number of support vectors. To be more precise, v is an upper bound on the fraction of training errors and a lower bound on the fraction of support vectors.Cited by: 97
http://alex.smola.org/papers/1999/SchBarSmoWil99.pdf
Shrinking the Tube: A New Support Vector Regression Algorithm Bernhard Scholkopf¨ x, Peter Bartlett , Alex Smola , Robert Williamson x GMD FIRST, Rudower Chaussee 5, 12489 Berlin, Germany FEIT/RSISE, Australian National University,Canberra 0200, Australia
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