Training Restricted Boltzmann Machines With a D-Wave Quantum Annealer

Training Restricted Boltzmann Machines With a D-Wave Quantum Annealer

Restricted Boltzmann Machine (RBM) is an energy-based, undirected graphical model. It is commonly used for unsupervised and supervised machine learning. Typically, RBM is trained using contrastive divergence (CD). However, training with CD is slow and does not estimate the exact gradient of the log-...

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Bibliographic Details
Main Authors: Vivek Dixit, Raja Selvarajan, Muhammad A. Alam, Travis S. Humble, Sabre Kais
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-06-01
Series:Frontiers in Physics
Subjects:
bars and stripes
quantum annealing
classification
image reconstruction
log-likelihood
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fphy.2021.589626/full

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https://www.frontiersin.org/articles/10.3389/fphy.2021.589626/full

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