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Training Restricted Boltzmann Machine Using Gradient Fixing Based Algorithm被引量：4: 《Chinese Journal of Electronics》2018年第4期694-703,共10页LI Fei GAO Xiaoguang WAN Kaifang; supported by the National Natural Science Foundation of China(No.61573285,No.61305133);the Fundamental Research Funds for the Central Universities(No.3102015BJ(Ⅱ)GH01,No.3102016CG002); Most of the algorithms for training restricted Boltzmann machines(RBM) are based on Gibbs sampling. When the sampling algorithm is used to calculate the gradient, the sampling gradient is the approximate value of the ...; 关键词：Deep Learning Restricted Boltzmann machine（RBM） Gradient fixing Gibbs sampling training algorithm（GFGS） Gradient fixing based parallel tempering algorithm（GFPT）

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