QRNN(Quasi-Recurrent Neural Networks)
keras代码:https://github.com/DingKe/qrnn QRNN为LSTM加速算法,模型结构如下: qrnn第一层为卷积层,用于提取输入特征,第二层为pooling层,用于减少特征数目,但语常用的pooling层不同的是,qrnn采用fo-pool方法,具体计算如下. 卷积层: 对于输入X,分别通过三个卷积层和非线性层得到Z,F,O,公式如下: Z=tanh(Wz∗X) F=
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