Generalized Conjugate Directions
RICE UNIV HOUSTON TX DEPT OF COMPUTATIONAL AND APPLIED MATHEMATICS
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This paper presents a simple unifying framework for a wide class of conjugate directions algorithms whose iterates minimize some quadratic functional over a subspace. Our approach is motivated by its advantages for nonlinear minimization, but the purpose of this paper is to present the greatly simplified convergence analysis that results for the linear case.
- Operations Research