Search for: [Abstract = "The paper presents a proximal bundle method for minimizing a convex function f over a convex set C. It requires evaluating f and its subgradients with a fixed but possibly unknown accuracy ε> 0. Each iteration involves solving an unconstrained proximal subproblem, and projecting a certain point onto C. The method asymptotically finds points that are ε\-optimal. In Lagrangian relaxation of convex programs, it allows for ε\-accurate solutions of Lagrangian subproblems, and finds ε\-optimal primal solutions. For semidefinite programming problems, it extends the highly successful spectral bundle method to the case of inexact eigenvalue computations."]

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