It is often observed that interpolation based on translates of radial basis functions or non-radial kernels is numerically unstable due to exceedingly large condition of the kernel matrix. But if stability is assessed in function space without considering special bases, this paper proves that kernel-based interpolation is stabl
Abstract: Interpolation by translates of \radial " basis functions is optimal in the sense tha...
Abstract. We study the computational complexity, the error behavior, and the numerical stability of ...
This paper is dedicated to Prof. Francesco A. Costabile on the occasion of his 70th birthday In this...
It is often observed that interpolation based on translates of radial basis functions or non-radial ...
In the paper "Stability of kernel-based interpolation" (to appear on Adv. Comput. Math.) we prove...
It is often observed that interpolation based on translates of radial basis functions or non-radial ...
In the recent paper [1], a new method to compute stable kernel-based interpolants has been presented...
It is well known that radial basis function interpolants suffer from bad conditioning if the basis o...
It is well-known that radial basis function interpolants suffer of bad conditioning if the basis of ...
A traditional criterion to calculate the numerical stability of the interpolation matrix is its stan...
AbstractIt is well known that representations of kernel-based approximants in terms of the standard ...
The polynomial kernels are widely used in machine learning and they are one of the default choices t...
AbstractSince it is well-known (De Marchi and Schaback (2001) [4]) that standard bases of kernel tra...
In this paper we propose a new stable and accurate approximation technique which is extremely effect...
In this paper we propose a new stable and accurate approximation technique which is extremely effect...
Abstract: Interpolation by translates of \radial " basis functions is optimal in the sense tha...
Abstract. We study the computational complexity, the error behavior, and the numerical stability of ...
This paper is dedicated to Prof. Francesco A. Costabile on the occasion of his 70th birthday In this...
It is often observed that interpolation based on translates of radial basis functions or non-radial ...
In the paper "Stability of kernel-based interpolation" (to appear on Adv. Comput. Math.) we prove...
It is often observed that interpolation based on translates of radial basis functions or non-radial ...
In the recent paper [1], a new method to compute stable kernel-based interpolants has been presented...
It is well known that radial basis function interpolants suffer from bad conditioning if the basis o...
It is well-known that radial basis function interpolants suffer of bad conditioning if the basis of ...
A traditional criterion to calculate the numerical stability of the interpolation matrix is its stan...
AbstractIt is well known that representations of kernel-based approximants in terms of the standard ...
The polynomial kernels are widely used in machine learning and they are one of the default choices t...
AbstractSince it is well-known (De Marchi and Schaback (2001) [4]) that standard bases of kernel tra...
In this paper we propose a new stable and accurate approximation technique which is extremely effect...
In this paper we propose a new stable and accurate approximation technique which is extremely effect...
Abstract: Interpolation by translates of \radial " basis functions is optimal in the sense tha...
Abstract. We study the computational complexity, the error behavior, and the numerical stability of ...
This paper is dedicated to Prof. Francesco A. Costabile on the occasion of his 70th birthday In this...
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