Reverse Annealing for Nonnegative/Binary Matrix Factorization

Abstract

It was recently shown that quantum annealing can be used as an effective, fast subroutine in certain types of matrix factorization algorithms. The quantum annealing algorithm performed best for quick, approximate answers, but performance rapidly plateaued. In this paper, we utilize reverse annealing instead of forward annealing in the quantum annealing subroutine for nonnegative/binary matrix factorization problems. After an initial global search with forward annealing, reverse annealing performs a series of local searches that refine existing solutions. The combination of forward and reverse annealing significantly improves performance compared to forward annealing alone for all but the shortest run times.

arXiv comment9 pages, 5 figures

References in corpus (5)

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• Nonnegative/binary matrix factorization with a D-Wave quantum annealer
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• Performance Improvement of True Time Delay Based Centralized Beamforming Control with the Modulation Instability Phenomenon for Wireless-Array Antennas
• Boolean Hierarchical Tucker Networks on Quantum Annealers
• Collaborative filtering based on nonnegative/binary matrix factorization