Stopping Criteria in Contrastive Divergence: Alternatives to the Reconstruction Error

20 Dec 2013David BuchacaEnrique RomeroFerran MazzantiJordi Delgado

Restricted Boltzmann Machines (RBMs) are general unsupervised learning devices to ascertain generative models of data distributions. RBMs are often trained using the Contrastive Divergence learning algorithm (CD), an approximation to the gradient of the data log-likelihood... (read more)

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