战略通常进行逼近目标的努力。
稀疏贪婪优化直接逼近目标函数的下降,因而可以明显地减小目标函数。
Sparse greedy optimization directly approximates the improvement of the objective function and thus can significantly decreases the objective function.
采用埃尔米特插值多项式代替泰勒展开式逼近目标函数,极大地降低了高阶交叉灵敏度的阶数。
Adopting the Hermite polynomial instead of the Taylor polynomial can greatly decrease the order of high-order cross sensitivity.
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