Fused lasso with a non-convex sparsity inducing penalty

@article{Bayram2014FusedLW,
  title={Fused lasso with a non-convex sparsity inducing penalty},
  author={Ilker Bayram and Po-Yu Chen and Ivan W. Selesnick},
  journal={2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2014},
  pages={4156-4160}
}
The fused lasso problem involves the minimization of the sum of a quadratic, a TV term and an ℓ1 term. The solution can be obtained by applying a TV denoising filter followed by soft-thresholding. However, soft-thresholding introduces a certain bias to the non-zero coefficients. In order to prevent this bias, we propose to replace the ℓ1 penalty with a non-convex penalty. We show that the solution can similarly be obtained by applying a modified thresholding function to the result of the TV… CONTINUE READING

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