TY - JOUR
T1 - Compressed sensing based on QUBO formulation
AU - Kudo, Kazue
N1 - Funding Information:
This work was partially supported by the JSPS KAKENHI (Grant Number JP18K11333).
Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2022/3/28
Y1 - 2022/3/28
N2 - Ising machines efficiently solve the combinatorial optimization problems described by the Ising model or the quadratic unconstrained binary optimization (QUBO) formulation. A hybrid method based on the QUBO formulation for compressed sensing is proposed. The proposed method comprises alternative steps of discrete and continuous optimization. In the discrete optimization step, the objective function is described by the QUBO formulation. Successful examples obtained via the proposed method are demonstrated. The performance of the proposed method depends highly on the initial conditions.
AB - Ising machines efficiently solve the combinatorial optimization problems described by the Ising model or the quadratic unconstrained binary optimization (QUBO) formulation. A hybrid method based on the QUBO formulation for compressed sensing is proposed. The proposed method comprises alternative steps of discrete and continuous optimization. In the discrete optimization step, the objective function is described by the QUBO formulation. Successful examples obtained via the proposed method are demonstrated. The performance of the proposed method depends highly on the initial conditions.
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U2 - 10.1088/1742-6596/2207/1/012033
DO - 10.1088/1742-6596/2207/1/012033
M3 - Conference article
AN - SCOPUS:85128940995
SN - 1742-6588
VL - 2207
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012033
T2 - 32nd IUPAP Conference in Computational Physics, CCP 2021
Y2 - 2 August 2021 through 5 August 2021
ER -