• Corpus ID: 221397083

Systematic comparison of deep belief network training using quantum annealing vs. classical techniques

@article{Job2020SystematicCO,
  title={Systematic comparison of deep belief network training using quantum annealing vs. classical techniques},
  author={Joshua Adam Job and Steven H. Adachi},
  journal={arXiv: Quantum Physics},
  year={2020}
}
  • J. Job, S. Adachi
  • Published 31 August 2020
  • Computer Science
  • arXiv: Quantum Physics
In this work we revisit and expand on a 2015 study that used a D-Wave quantum annealer as a sampling engine to assist in the training of a Deep Neural Network. The original 2015 results were reproduced using more recent D-Wave hardware. We systematically compare this quantum-assisted training method to a wider range of classical techniques, including: Contrastive Divergence with a different choice of optimizer; Contrastive Divergence with an increased number of steps (CD-k); and Simulated… 

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