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http://www.stat.purdue.edu/~yuzhu/stat598m3/Papers/NewSVM.pdf
New Support Vector Algorithms ... We propose a new class of support vector algorithms for regression and classi” cation. In these algorithms, a parameterºlets one effectively con-trol the number of support vectors. While this can be useful in its own right, the parameterization has the additional bene” t of enabling us to
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 regression case ...
https://www.scirp.org/reference/referencespapers.aspx?referenceid=9409
B. Schlkopf, A. J. Smola, R. C. Williamson, and P. L. Bartlett, “New support vector algorithms,” Neural Computation, Vol. 12, No. 5, pp. 1207–1245, 2000.
https://www.researchgate.net/publication/12413257_New_Support_Vector_Algorithms
We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter nu lets one effectively control the number of support vectors.
http://www-optima.amp.i.kyoto-u.ac.jp/~fuku/papers/Zhong_Fukushima_final.pdf
A NEW MULTI-CLASS SUPPORT VECTOR ALGORITHM 5 3 THE ”-K-SVCR LEARNING MACHINE 3.1 The Formulation of ”-K-SVCR Let the training set T be given by (1). For an arbitrary pair (Θj;Θk) 2 Y £ Y of classes, we wish to construct a decision function f(x) based on a hyperplane similar to (2) which separates the two classes Θj and Θk as well as the remaining classes.
https://b-ok.cc/book/644281/7a527a
Bernhard Schlkopf, Alexander J. Smola In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs—-kernels--for a number of learning tasks.
http://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 …
https://www.deepdyve.com/lp/mit-press/new-support-vector-algorithms-4I2gUjGvJh
May 01, 2000 · 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. 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 ...
https://pdfs.semanticscholar.org/2862/e7b8fefb209cdb4c47a1643f2af71cd67b00.pdf
B. Sch olkopf and A.J. Smola, Support Vector Machines and Kernel Algorithms, 2 INTRODUCTION One of the fundamental problems of learning theory is the following: suppose we are given two classes of objects. We are then faced with a new object, and we have to assign it to one of the two classes. This
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 …
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