Abstract
A special variable metric method is given for finding minima of convex functions that are not necessarily differentiable. Time-consuming quadratic programming subproblems do not need to be solved. Global convergence of the method is established. Some encouraging numerical experience is reported.
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Lukšan, L., Vlček, J. Globally Convergent Variable Metric Method for Convex Nonsmooth Unconstrained Minimization1. Journal of Optimization Theory and Applications 102, 593–613 (1999). https://doi.org/10.1023/A:1022650107080
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DOI: https://doi.org/10.1023/A:1022650107080