Title :
A Simple and Fast Multi-instance Classification via Support Vector Machine
Author :
Zhiquan Qi ; Yingjie Tian ; Yong Shi
Author_Institution :
Res. Center on Fictitious Econ. & Data Sci., Beijing, China
Abstract :
In this paper, we proposed a Simple and Fast Multi-Instance Classification Via Support Vector Machine (called Fast MI-SVM). Compared with the other conventional Multi-Instance learning method, our method is able to deal with multi-instance learning problem by only solving a quadratic programming problem. So the training time of Fast MI-SVM is very fast. All numerical experiments on benchmark datasets show the feasibility and validity of the proposed method.
Keywords :
convex programming; learning (artificial intelligence); quadratic programming; support vector machines; multi-instance classification; multi-instance learning method; quadratic programming problem; support vector machine; convex optimization; multi-Instance Classification; support vector machine;
Conference_Titel :
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2012 IEEE/WIC/ACM International Conferences on
Conference_Location :
Macau
Print_ISBN :
978-1-4673-6057-9
DOI :
10.1109/WI-IAT.2012.50
