1. In a deep belief network (DBN), a method for training the DBN for operational decoding comprising: pre-training initial weights based on determined optimal weights; identifying, during pre-training, a batch size and number of parameters corresponding to the initial weights, the batch size larger than that allowable for purely generative pretraining; and invoking a plurality of machines for performing training in parallel fashion.