Conjugate gradient methods are important iterative methods for solving optimization problems.
共轭梯度法是求解最优化问题的一类有效算法。
This paper gives the global convergence of a class of conjugate gradient methods with relaxed line search.
在推广线搜索下给出了一类共轭梯度法的全局收敛结果。
Pr conjugate gradient method is one of the efficient methods for solving large scale unconstrained optimization problems, however, its global convergence has not been solved for a long time.
PR共轭梯度法是求解大型无约束优化问题的有效算法之一，但是算法的全局收敛性在理论上一直没有得到解决。
The conjugate gradient method is one of the most efficient methods for solving unconstrained optimization problems.
共轭梯度法是求解无约束优化问题的一类有效方法。
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.
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。
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