Graph-based semi-supervised learning

作     者：Changshui ZHANG Fei WANG 

作者机构：State Key Laboratory of Intelligent Technologies and SystemsTsinghua National Laboratory for Information Science and Technology(TNList)Department of AutomationTsinghua UniversityBeijing 100084China 

出 版 物：《Frontiers of Electrical and Electronic Engineering in China》 (中国电气与电子工程前沿（英文版）)

年 卷 期：2011年第6卷第1期

页      面：17-26页

学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学] 

基　　金：supported by the National Natural Science Foundation of China(Grant Nos.60835002 61075004) 

主　　题：graph-based semi-supervised learning(GBSSL) linear neighborhood propagation(LNP) point charge model fMRI image segmentation 

摘      要：The recent years have witnessed a surge of interests in graph-based semi-supervised learning(GBSSL).In this paper,we will introduce a series of works done by our group on this topic including:1)a method called linear neighborhood propagation(LNP)which can automatically construct the optimal graph;2)a novel multilevel scheme to make our algorithm scalable for large data sets;3)a generalized point charge scheme for GBSSL;4)a multilabel GBSSL method by solving a Sylvester equation;5)an information fusion framework for GBSSL;and 6)an application of GBSSL on fMRI image segmentation.