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Keywords:
conjugate gradient method; unconstrained optimization; conic function; interpolations; algorithm
conjugate gradient method; unconstrained optimization; conic function; interpolations; algorithm
Summary:
The paper contains a description and an analysis of two modifications of the conjugate gradient method for unconstrained minimization which find a minimum of the conic function after a finite number of steps. Moreover, further extension of the conjugate gradient method is given which is based on a more general class of the model functions.
References:
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