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On the V(subscript gamma) Dimension for Regression in Reproducing Kernel Hilbert Spaces
This paper presents a computation of the $V_gamma$ dimension for regression in bounded subspaces of Reproducing Kernel Hilbert Spaces (RKHS) for the Support Vector Machine (SVM) regression $epsilon$-insensitive loss function, ...
A Unified Framework for Regularization Networks and Support Vector Machines
Regularization Networks and Support Vector Machines are techniques for solving certain problems of learning from examples -- in particular the regression problem of approximating a multivariate function from sparse ...