The simplest way to obtain continuous interpolation between two points in
high dimensional space is to draw a line between them. While previous works
focused on the general connectivity between model parameters,
该研究通过概率隐变量序列模型,使用前向算法实现连续状态 Kalman 滤波器来学习单词的表示。通过 EM 算法准确地优化参数,使用所学习到的单词嵌入作为标记任务的特征,在标记任务中实现显著的准确度改进,并通过线性递归神经网络通过我们的模型的参数来初始化非线性递归神经网络语言模型,降低了其训练时间和困惑度。