Generating optimal trajectories for a large numbers of vehicles in real-time becomes
extremely challenging when including realistic dynamic models and time-varying obstacle …

We present a breadth-oriented collection of cross-platform command-line tools for
researchers in machine learning called Waffles. The Waffles tools are designed to offer a …

Many manifold learning algorithms utilise graphs of local neighbourhoods to estimate
manifold topology. When neighbourhood connections short-circuit between geodesically …

Manifold learning is a class of machine learning methods that exploits the observation that
high-dimensional data tend to lie on a smooth lower-dimensional manifold. Manifold …

The safe and stable operation of roadheader is of great significance to the efficient and rapid
production of a coal mine. Health diagnosis based on vibration signals has been studied in …

In manifold learning, alignment is performed with the objective of deriving the global low‐
dimensional coordinates of input data from their local coordinates. In virtually all alignment …

Applications of Nonlinear Optimization Page 1 Washington University in St. Louis
Washington University Open Scholarship Arts & Sciences Electronic Theses and …

我们提出一种新的流形学习算法, 称为局部正交性保持对齐(LOPA). 该算法受局部切空间对齐(
LTSA) 方法的启发; LTSA 方法采用仿射变换, 试图将多个局部邻域对齐到一个全局坐标系中 …

Genetic algorithms (GAs) have been used to find efficient solutions to numerous
fundamental and applied problems. While GAs are a robust and flexible approach to solve …

In this paper, we propose a new algorithm to implement the generalized multiple maximum
scatter difference (GMMSD). Due to enhanced features of this algorithm over the original …