网络非凸函数 网络释义 1. 非凸函数 非凸性规划,Non... ... ) nonconvex boundary 非凸边界 )nonconvex function非凸函数) nonconvex minimization 非凸极小 ... www.dictall.com|基于3个网页
Minimization of a Non-Convex FunctionConvexityGlobal optimizationSummary This chapter contains sections titled: Probabilities, convexity and global optimizationdoi:10.1002/9781118622438.ch4Eduardo Souza de CursiRubens SampaioPiotr BreitkopfJohn Wiley & Sons, Inc....
接下来,我分两个情况来讨论收敛性:1.Convex。2. Strongly convex。 1.1.convex case 定理1.1(Nonsmooth + convex)如果函数 f 是凸的且是Lipschitzness的。对于迭代方法(1.1),步长选择策略为: \alpha_k =\frac{f(x^k) - f^*}{\|g^k\|^2} 如果g^k \neq 0 ,否则 \alpha_k = 1 。那么我们有:...
一般这种Black Box function都是iteratively find the minimizer of non convex function. Nonconvex从算法...
Solving the optimal control of stochastic differential equations (SDEs) using the dynamic programming method requires writing the problem in terms of the so-called value function. This paper presents conditions to assure that the value function is convex away from the origin, a concept that allows...
In this paper, we propose a robust scheme for least squares support vector regression (LS-SVR), termed as RLS-SVR, which employs non-convex least squares loss function to overcome the limitation of LS-SVR that it is sensitive to outliers. Non-convex loss gives a constant penalty for any ...
We construct a Lipschitz function on $\\mathbb R^2$ which is locally convex on the complement of some totally disconnected compact set but not convex. Existence of such function disproves a theorem that appeared in a paper by L. Pasqualini and was also cited by other authors.Pokorny, Dusan...
which is a convex functional and makes the problem easier to solve. It has been shown that under some assumptions, the regularization problems with suchrelaxation leads to a near optimal sparse solution. To further encourage the sparsity of the solutions, some nonconvex regularizers are proposed ...
摘要: It is shown that a convex function, defined on an arbitrary, possibly finite, subset of a linear space, can be extended to the whole space. An application to decision making under risk is given.DOI: 10.1016/0165-1765(86)90242-9 ...
We present a fast and robust nonconvex optimization approach for Fuzzy C-Means (FCM) clustering model. Our approach is based on DC (Difference of Convex functions) programming and DCA (DC Algorithms) that have been successfully applied in various fields of applied sciences, including Machine Learn...