A unified approach on fast training of feedforward and recurrent networks using EM algorithm
In this work, we provide a theoretical framework that unifies the notions of hidden representations and moving targets through the expectation and maximization (EM) algorithm. Based on such a framework, two fast training algorithms can be derived consistently for both feedforward networks and recurrent networks.