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The restricted Boltzman machine is an unsupervised learning algorithm which is similar to the wake-sleep algorithm. It uses stochastic learning, ie. neural activations are stochastic with continuous probabilities given by weights.

The weights in a trained RBM implicitly encode a PDF over the training set.

Learning in RBMs is competitive but without explicit inhibition (because the RBM is restricted in that it does not have recurrent connections). Neurons learn different things due to random initialization and stochastic processing.