most citedMeshless Hermite-HDMR finite difference method for high-dimensional Dirichlet problems

1 citations · 2 across the 5 of their papers we have counts for

collaborators

7 papers

math.OC2020

Derivative-free global minimization for a class of multiple minima problems

Xiaopeng Luo, Xin Xu, Daoyi Dong

We prove that the finite-difference based derivative-free descent (FD-DFD) methods have a capability to find the global minima for a class of multiple minima problems. Our main res…

math.OC2020

Asymptotic proximal point methods: finding the global minima with linear convergence for a class of multiple minima problems

Xiaopeng Luo, Xin Xu, Herschel A. Rabitz

We propose and analyze asymptotic proximal point (APP) methods to find the global minimizer for a class of nonconvex, nonsmooth, or even discontinuous multiple minima functions. Th…

math.OC2020

Can speed up the convergence rate of stochastic gradient methods to by a gradient averaging strategy?

Xin Xu, Xiaopeng Luo

In this paper we consider the question of whether it is possible to apply a gradient averaging strategy to improve on the sublinear convergence rates without any increase in storag…

math.OC20201 cited

Stochastic gradient-free descents

Xiaopeng Luo, Xin Xu

In this paper we propose stochastic gradient-free methods and accelerated methods with momentum for solving stochastic optimization problems. All these methods rely on stochastic d…

math.NA2019

Numerical meshless solution of high-dimensional sine-Gordon equations via Fourier HDMR-HC approximation

Xin Xu, Xiaopeng Luo, Herschel Rabitz

In this paper, an implicit time stepping meshless scheme is proposed to find the numerical solution of high-dimensional sine-Gordon equations (SGEs) by combining the high dimension…

math.NA20191 cited

Meshless Hermite-HDMR finite difference method for high-dimensional Dirichlet problems

Xiaopeng Luo, Xin Xu, Herschel Rabitz

In this paper, a meshless Hermite-HDMR finite difference method is proposed to solve high-dimensional Dirichlet problems. The approach is based on the local Hermite-HDMR expansion…