Building on (Neal and Hinton, 1998), where the problem tackled by EM is recast as the optimization of a free energy functional on an infinite-dimensional space, we obtain three practical particle-based alternatives to EM applicable to broad classes of models. All three are derived through straightforward discretizations of gradient flows associated with the functional. The novel algorithms scale well to high-dimensional settings and outperform existing state-of-the-art methods in numerical experiments.

翻译：在(Neal和Hinton,1998年)的基础上,EM所处理的问题被改造成在无限空间优化免费能源功能,我们获得了三种适用于大类模型的EM的实用粒子替代物,所有三种都是通过与功能相关的梯度流的直截了当的分解而得出的。新奇算法向高维环境发展良好,在数字实验中优于现有最先进的方法。