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
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)