Distributed Boosting Algorithm over Multi-agent Networks
作者单位：Key Lab of Systems and Control Academy of Mathematics and Systems Science University of Chinese Academy of Sciences
会议名称：《第37届中国控制会议》
会议日期：2018年
学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：supported by NSFC under grants 61733018 61573344 61333001
关 键 词：Multi-agent systems distributed design boosting classification
摘 要：This paper investigates a distributed design for boosting methods, especially Ada Boost, over multi-agent *** fact, we present a distributed Ada Boost algorithm for solving a distributed classification problem in machine learning through sharing classifiers among agents. Our algorithm can effectively avoid overfitting, efficiently merge the feature information of other agents, and moreover, largely reduce the communication cost in comparison with some existing centralized or distributed algorithms. Furthermore, simulations with a real classification dataset is given to show the effectiveness of the proposed algorithm. The performance of the proposed algorithm matches that of the centralized Ada Boost algorithm.