Parallelized Training of Restricted Boltzmann Machines Using Markov-Chain Monte Carlo Methods

Restricted Boltzmann machine (RBM) is a generative stochastic neural network that can be applied to collaborative filtering technique used by recommendation systems. Prediction accuracy of the RBM model is usually better than that of other models for recommendation systems. However, training the RBM...

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Veröffentlicht in:	SN computer science 2020-05, Vol.1 (3), p.165, Article 165
Hauptverfasser:	Yang, Pei, Varadharajan, Srinivas, Wilson, Lucas A., Smith, Don D., Lockman, John A., Gundecha, Vineet, Ta, Quy
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Collaboration Computer Imaging Computer Science Computer Systems Organization and Communication Networks Data Structures and Information Theory Datasets Decomposition Information Systems and Communication Service Markov analysis Markov chains Monte Carlo simulation Neural networks Neurons Original Research Pattern Recognition and Graphics Probability distribution Ratings & rankings Recommender systems Software Challenges to Exascale Computing Software Engineering/Programming and Operating Systems Training Vision
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