Title :
Finding convex hull vertices in metric space
Author :
Jinhong Zhong ; Ke Tang ; Qin, A.K.
Author_Institution :
Sch. of Comput. Sci. & Technol., USTC, Hefei, China
Abstract :
The convex hull has been extensively studied in computational geometry and its applications have spread over an impressive number of fields. How to find the convex hull is an important and challenging problem. Although many algorithms had been proposed for that, most of them can only tackle the problem in two or three dimensions and the biggest issue is that those algorithms rely on the samples´ coordinates to find the convex hull. In this paper, we propose an approximation algorithm named FVDM, which only utilizes the information of the samples´ distance matrix to find the convex hull. Experiments demonstrate that FVDM can effectively identify the vertices of the convex hull.
Keywords :
approximation theory; computational geometry; matrix algebra; FVDM; approximation algorithm; computational geometry; convex hull vertices; distance matrix; metric space; Algorithm design and analysis; Approximation algorithms; Classification algorithms; Kernel; Sufficient conditions; Support vector machines; Transmission line matrix methods; convex hull; metric space;
Conference_Titel :
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6627-1
DOI :
10.1109/IJCNN.2014.6889699