Data centering in feature space

@inproceedings{Meila2003DataCI,
  title={Data centering in feature space},
  author={Marina Meila},
  booktitle={AISTATS},
  year={2003}
}
This paper presents a family of methods for shifting the data in feature space to be used in conjunction with kernel machines. The shift can be performed using only kernel evaluations in input space. The methods are used to improve the numerical properties of kernel machines and to generate new families of string kernels. Experiments on real and artificial data show the beneficial effects of the centering methods and reveal further insights into the geometry of origin shifts in feature space. 
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