SMOOTHING QUADRATIC REGULARIZATION METHODS FOR BOX CONSTRAINED NON-LIPSCHITZ OPTIMIZATION IN IMAGE RESTORATION

@inproceedings{Bian2014SMOOTHINGQR,
  title={SMOOTHING QUADRATIC REGULARIZATION METHODS FOR BOX CONSTRAINED NON-LIPSCHITZ OPTIMIZATION IN IMAGE RESTORATION},
  author={Wei Bian and Xiaojun Chen},
  year={2014}
}
Abstract. We propose a smoothing quadratic regularization (SQR) method for solving box constrained optimization problems with a non-Lipschitz regularization term that includes the lp norm (0 < p < 1) of the gradient of the underlying image in the l2-lp problem as a special case. At each iteration of the SQR algorithm, a new iterate is generated by solving a strongly convex quadratic problem with box constraints. We prove that any cluster point of ε scaled first order stationary points with… CONTINUE READING

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