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An adaptive conjugate gradient algorithm is presented. The search direction is computed as the sum of the negative gradient and a vector determined by minimizing the quadratic approximation of objective function at the current point. Using a special approximation of the inverse Hessian of the objective function, which depends by a positive parameter, we get the search direction which satisfies both...
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