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DOE OSTI · 1332219

Generative Modeling for Machine Learning on the D-Wave

Thulasidasan, Sunil
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Abstract

These are slides on Generative Modeling for Machine Learning on the D-Wave. The following topics are detailed: generative models; Boltzmann machines: a generative model; restricted Boltzmann machines; learning parameters: RBM training; practical ways to train RBM; D-Wave as a Boltzmann sampler; mapping RBM onto the D-Wave; Chimera restricted RBM; mapping binary RBM to Ising model; experiments; data; D-Wave effective temperature, parameters noise, etc.; experiments: contrastive divergence (CD) 1 step; after 50 steps of CD; after 100 steps of CD; D-Wave (experiments 1, 2, 3); D-Wave observations.

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Thulasidasan, Sunil. 2016-11-15. Generative Modeling for Machine Learning on the D-Wave. https://doi.org/10.2172/1332219

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