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  2. Restricted Boltzmann machine - Wikipedia

    en.wikipedia.org/wiki/Restricted_Boltzmann_machine

    Diagram of a restricted Boltzmann machine with three visible units and four hidden units (no bias units) 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.

  3. Feature learning - Wikipedia

    en.wikipedia.org/wiki/Feature_learning

    Restricted Boltzmann machines (RBMs) are often used as a building block for multilayer learning architectures. [ 6 ] [ 24 ] An RBM can be represented by an undirected bipartite graph consisting of a group of binary hidden variables , a group of visible variables, and edges connecting the hidden and visible nodes.

  4. Wake-sleep algorithm - Wikipedia

    en.wikipedia.org/wiki/Wake-sleep_algorithm

    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]

  5. Boltzmann machine - Wikipedia

    en.wikipedia.org/wiki/Boltzmann_machine

    This is not a restricted Boltzmann machine. A Boltzmann machine (also called Sherrington–Kirkpatrick model with external field or stochastic Ising model), named after Ludwig Boltzmann is a spin-glass model with an external field, i.e., a Sherrington–Kirkpatrick model, [1] that is a stochastic Ising model.

  6. Types of artificial neural networks - Wikipedia

    en.wikipedia.org/wiki/Types_of_artificial_neural...

    The Boltzmann machine can be thought of as a noisy Hopfield network. It is one of the first neural networks to demonstrate learning of latent variables (hidden units). Boltzmann machine learning was at first slow to simulate, but the contrastive divergence algorithm speeds up training for Boltzmann machines and Products of Experts.

  7. Autoencoder - Wikipedia

    en.wikipedia.org/wiki/Autoencoder

    An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data (unsupervised learning).An autoencoder learns two functions: an encoding function that transforms the input data, and a decoding function that recreates the input data from the encoded representation.

  8. Pelicans' Zion Williamson reportedly not close to return from ...

    www.aol.com/sports/pelicans-zion-williamson...

    The Pelicans expected him to miss four to six weeks when he suffered the injury on Nov. 6 versus the Cleveland Cavaliers, according to ESPN's Shams Charania. Following that timeline, Williamson ...

  9. Category:Supervised learning - Wikipedia

    en.wikipedia.org/wiki/Category:Supervised_learning

    Restricted Boltzmann machine; V. Variational autoencoder This page was last edited on 10 October 2019, at 06:27 (UTC). Text is available under the Creative ...