Stacked Restricted Boltzmann Machine
A restricted Boltzmann machine (RBM) (also called a restricted Sherrington–Kirkpatrick model with external field or restricted stochastic Ising–Lenz–Little model) is a generative stochastic artificial neural network that can learn a probability distribution over its set of inputs. RBMs were initially proposed under the name Harmonium by Paul Smolensky in 1986, and rose to prominence after Geoffrey Hinton and collaborators used fast learning algorithms for them in the mid-2000s. RBMs have found applications in dimensionality reduction, classification, collaborative filtering, feature learning, topic modelling,Ruslan Salakhutdinov and Geoffrey Hinton (2010)Replicated softmax: an undirected topic model. '' Neural Information Processing Systems'' 23. immunology Immunology is a branch of biology and medicine that covers the study of Immune system, immune systems in all Organism, organisms. Immunology charts, measures, and contextualizes the Physiology, physiological fun ...
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