This paper deals with the geometric numerical integration of gradient flow and its application to optimization. Gradient flows often appear as model equations of various physical phenomena, and their dissipation laws are essential. Therefore, dissipative numerical methods, which are numerical methods replicating the dissipation law, have been studied in the literature. Recently, Cheng, Liu, and Shen proposed a novel dissipative method, the Lagrange multiplier approach, for gradient flows, which is computationally cheaper than existing dissipative methods. Although their efficacy is numerically confirmed in existing studies, the existence results of the Lagrange multiplier approach are not known in the literature. In this paper, we establish some existence results. We prove the existence of the solution under a relatively mild assumption. In addition, by restricting ourselves to a special case, we show some existence and uniqueness results with concrete bounds. As gradient flows also appear in optimization, we further apply the latter results to optimization problems.
翻译:本文涉及梯度流的几何数字整合及其适用于优化。 渐变流通常作为各种物理现象的模型方程式出现, 它们的消散法是不可或缺的。 因此, 文献中已经研究了消散数字方法, 它们是复制消散法的数值方法。 最近, Cheng, Liu和Shen 提出了一个新的消散方法, 即拉格朗乘数方法, 用于梯度流, 其计算成本比现有的消散方法要低。 尽管它们的效力在数字上得到了确认, 文献中并不了解拉格朗乘数方法的存在结果。 在本文中, 我们确立了一些存在结果。 我们证明, 在相对温和的假设下, 存在解决方案的存在。 此外, 我们通过将自身局限于一个特殊的情况, 显示某些存在和独特性的结果, 具体界限。 在优化中也出现梯度流, 我们进一步应用后一种结果来优化问题 。