Conjugate gradient algorithms for large optimization problems are studied. These methods accelerate (or precondition) the conjugate gradient method by means of quasi-Newton matrices, and are designed to utilize a variable amount of storage, depending on how much information is retained in the quasi-Newton matrices. The behavior of such methods on the underlying quadratic model, and in particular, the finite termination properties are considered.
|Original language||English (US)|
|Title of host publication||Mathematical Programming|
|Number of pages||15|
|State||Published - Aug 1 1982|
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