会议专题

Optimization Method of Deep Learning Algorithm Based on Extreme Learning Machine

  The Traditional global optimization algorithms is generally explored in whole deep belief network (DBN) with consuming amount of time, while the optimal method based on gradient used in DBN tends to local optimization.For solving this issue, in this paper, we propose a novel method which use extreme learning machine (ELM) into the training procedure of DBN to accelerate the learning process of DBN.Extensive experiment on the three widely available datasets demonstrate that our proposal effectively improves the accuracy and efficiency of the learning process of DBN,the result shows that our approach has a higher learning speed with a reliable learning accuracy.

Deep belief network Deep learning algorithm Extreme learning machine

Bo Lu Xiaodong Duan Zhijie Li

Dalian Key Lab of Digital Technology for National Culture,Dalian Nationalities University, Dalian, China

国际会议

International Conference on Computational Science and Engineering Applications(CSEA2015)2015计算机科学与工程应用国际会议

三亚

英文

238-243

2015-12-26(万方平台首次上网日期,不代表论文的发表时间)