On some steplength approaches for proximal algorithms

Applied Mathematics and Computation, pp. 345-362, 2015.

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Abstract:

We discuss a number of novel steplength selection schemes for proximal-based convex optimization algorithms. In particular, we consider the problem where the Lipschitz constant of the gradient of the smooth part of the objective function is unknown. We generalize two optimization algorithms of Khobotov type and prove convergence. We also ...More

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