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An algorithm for nonsmooth convex minimization with errors. (English) Zbl 0584.65034
Author’s summary: A readily implementable algorithm is given for minimizing any convex, not necessarily differentiable, function f of several variables. At each iteration the method requires only one approximate evaluation of f and its $$\epsilon$$-subgradient, and finds a search direction by solving a small quadratic programming problem. The algorithm generates a minimizing sequence of points, which converges to a solution whenever f has any minimizers.
Reviewer: I.H.Mufti

##### MSC:
 65K05 Numerical mathematical programming methods 90C25 Convex programming
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