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公开(公告)号:US20140164299A1
公开(公告)日:2014-06-12
申请号:US13707088
申请日:2012-12-06
IPC分类号: G06N3/08
CPC分类号: G06N3/08
摘要: Pretraining for a DBN initializes weights of the DBN (Deep Belief Network) using a hybrid pre-training methodology. Hybrid pre-training employs generative component that allows the hybrid PT method to have better performance in WER (Word Error Rate) compared to the discriminative PT method. Hybrid pre-training learns weights which are more closely linked to the final objective function, allowing for a much larger batch size compared to generative PT, which allows for improvements in speed; and a larger batch size allows for parallelization of the gradient computation, speeding up training further.
摘要翻译: 预先训练DBN使用混合预训练方法初始化DBN(深信仰网络)的权重。 混合预训练采用生成部件,与辨别性PT方法相比,允许混合PT方法在WER(字错误率)方面具有更好的性能。 混合预训练学习与最终目标函数更紧密相关的权重,允许与生成PT相比更大的批量大小,这允许提高速度; 并且较大的批量允许梯度计算的并行化,进一步加速训练。