We study approximations of optimization problems with probabilistic constraints in which the original distribution of the underlying random vector is replaced with an empirical dis...
This paper presents a global optimization operator for arbitrary meshes. The global optimization operator is composed of two main terms, one part is the global Laplacian operator ...
Ligang Liu, Chiew-Lan Tai, Zhongping Ji, Guojin Wa...
Given a set of rectangles with fixed orientations, we want to find an enclosing rectangle of minimum area that contains them all with no overlap. Many simple scheduling tasks ca...
The general stochastic optimal control (SOC) problem in robotics scenarios is often too complex to be solved exactly and in near real time. A classical approximate solution is to ...
Abstract—In this paper, we propose to leverage cloud computing to tame resource-poor mobile devices. Specifically, mobile applications can be executed in the mobile device (know...