共轭梯度法是最优化中最常用的方法之一，它具有算法简便、不需要矩阵存储等优点，十分适合于大规模优化问题。
Conjugate gradient method, which can be easily computed and requires no matrix storage, is one of the most popular and useful method for solving large scale optimization problems.
共轭梯度法是求解最优化问题的一类有效算法。
Conjugate gradient methods are important iterative methods for solving optimization problems.
约束最优化方法包括梯度法、共轭方向法、牛顿法和拟牛顿法。
Unconstrained optimization methods include gradient, conjugate direction, Newton, and quasi-Newton methods.
约束最优化方法包括梯度法、共轭方向法、牛顿法和拟牛顿法。
Unconstrained optimization methods include gradient, conjugate direction, Newton, and quasi-Newton methods.
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