%0 Journal Article
%T Stochastic Sample Based Algorithm for Learning Bayesian Networks<br>一种基于随机抽样的贝叶斯网络结构学习算法
%A HU Chun-ling
%A HU Xue-gang
%A <br>胡春玲
%A 胡学钢
%J 计算机科学
%D 2009
%I 
%X Based on the ideas of parallel stochastic sampling,this paper put forward an algorithm PCMHS for learning Bayesian networks.The PCMHS algorithm runs multi parallel Markov chains converging to Boltzmann distributions.The algorithm PCMHS,based on the mutual information between nodes,initializes all Markov chains.In the process of iteration,the algorithm,based on the population from parallel Metropolis-Hasting samplers,generates the proposal distribution for the next generation,and uses arc sample and sub-stru...
%K Bayesian networks
%K Structure learning
%K Stochastic sampling
%K Markov chain
%K Proposal distribution<br>贝叶斯网络
%K 结构学习
%K 随机抽样
%K 马尔可夫链
%K 建议分布
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=1C95DFF7ABB80836D3EC5F257D877AAC&yid=DE12191FBD62783C&vid=933658645952ED9F&iid=0B39A22176CE99FB&sid=FCD27DC5E1F2EEE7&eid=974CBB04624305A1&journal_id=1002-137X&journal_name=计算机科学&referenced_num=1&reference_num=13