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arXiv:2001.03715 · Journal of the Physical Society of Japan

Derivation of QUBO Formulations for Sparse Estimation

Tomohiro Yokota, Makiko Konoshima, Hirotaka Tamura, Jun Ohkubo

Published Feb 27, 2020• 2 citations
arXivHTMLPDF

Abstract

We propose a quadratic unconstrained binary optimization (QUBO) formulation of the l1-norm, which enables us to perform sparse estimation of Ising-type annealing methods such as quantum annealing. The QUBO formulation is derived using the Legendre transformation and the Wolfe theorem, which have recently been employed to derive the QUBO formulations of ReLU-type functions. It is shown that a simple application of the derivation method to the l1-norm case results in a redundant variable. Finally a simplified QUBO formulation is obtained by removing the redundant variable.

DOI
10.7566/jpsj.89.034801

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