燕山大学学报Issue(2)：145-151,7.DOI:10.3969/J.ISSN.1007-791X.2015.02.008
基于改进 Hadoop 的受限玻尔兹曼机云计算实现
Realization of RBM cloud computing based on improved Hadoop
摘要
Abstract
To resolve the slow training of Restricted Boltzmann Machine for handling large data the realization of RBM training based on cloud platform Hadoop is designed.In view of the training method of RBM Hadoop tasks message mechanism was improved to suit RBM′s short iteration cycle MapReduce framework was designed including Map function implemented Gibbs sampling and Reduce function completed parameter update based on Hadoop task combinations RBM′s cloud training was used in Deep Boltz⁃mann Machine′s training.The handwritten numeral recognition experiments show that this cloud training method can accelerate RBM training effective under large⁃scale data condition and work well in deep learning model training.关键词
云平台/受限玻尔兹曼机/Hadoop/并行编程Key words
cloud platform/restricted Boltzmann machine/Hadoop/parallel programming分类
信息技术与安全科学引用本文复制引用
刘凯,张立民,范晓磊,孙永威..基于改进 Hadoop 的受限玻尔兹曼机云计算实现[J].燕山大学学报,2015,(2):145-151,7.基金项目
国家自然科学基金资助项目 （）
