RBMs get their name due to there being “no communication between layers in the model, which is the ‘restriction’ of the model”36and that an RMB’s nodes “make ‘stochastic’ [or random] decisions”.36Because of this random process, RBMs are sometimes labeled as “stochastic neural netw...
Stochastic refers to a variable process where the outcome involves some randomness and has some uncertainty. It is a mathematical term and is closely related to “randomness” and “probabilistic” and can be contrasted to the idea of “deterministic.” The stochastic nature of machine learning alg...
The algorithms underlying deep neural networks–including backpropagation and stochastic gradient descent–have been around for a long time. So why is it that deep learning has only begun to show significant promise?Primarily it is because only now is it possible to provide these algorithms with ...
The general framework to describe and predict the behavior of macroscopic matter, statistical mechanics, was laid down in the 19th century by Boltzmann and Gibbs. The first ingredient of this theoretical framework is the atomistic hypothesis: matter is made ofparticlesobeying Newton’s equations. Comp...