Sparse incremental regression modeling using correlation criterion with boosting search

@article{Chen2005SparseIR,
  title={Sparse incremental regression modeling using correlation criterion with boosting search},
  author={S. Chen and X. X. Wang and D. J. Brown},
  journal={IEEE Signal Processing Letters},
  year={2005},
  volume={12},
  pages={198-201}
}
A novel technique is presented to construct sparse generalized Gaussian kernel regression models. The proposed method appends regressors in an incremental modeling by tuning the mean vector and diagonal covariance matrix of an individual Gaussian regressor to best fit the training data, based on a correlation criterion. It is shown that this is identical to incrementally minimizing the modeling mean square error (MSE). The optimization at each regression stage is carried out with a simple… CONTINUE READING
Highly Cited
This paper has 31 citations. REVIEW CITATIONS

References

Publications referenced by this paper.
Showing 1-10 of 25 references

Similar Papers

Loading similar papers…