Half-Quadratic Minimization of Regularized Objectives as the Fixed Point Iteration for the Linearized Gradient
نویسندگان
چکیده
We focus on the minimization of regularized objective functions using the popular half-quadratic approach introduced by Geman and Reynolds in 1992. We show that whenever applicable, this approach is equivalent to the very classical gradient linearization approach, known also as the fixed point iteration.
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