Wake-sleep_algorithm
Wake-sleep algorithm
Unsupervised learning algorithm
The wake-sleep algorithm[1] is an unsupervised learning algorithm for deep generative models, especially Helmholtz Machines.[2] The algorithm is similar to the expectation-maximization algorithm,[3] and optimizes the model likelihood for observed data.[4] The name of the algorithm derives from its use of two learning phases, the “wake” phase and the “sleep” phase, which are performed alternately.[1] It can be conceived as a model for learning in the brain,[5] but is also being applied for machine learning.[6]