A trust region algorithm with a worst-case iteration complexity of O(ϵ-3/2) for nonconvex optimization

We propose a trust region algorithm for solving nonconvex smooth optimization problems. For any ϵ ¯ ∈ ( 0 , ∞ ) , the algorithm requires at most O ( ϵ - 3 / 2 ) iterations, function evaluations, and derivative evaluations to drive the norm of the gradient of the objective function below any ϵ ∈ ( 0...

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