论文标题
QUBO制剂的推导以进行稀疏估计
Derivation of QUBO formulations for sparse estimation
论文作者
论文摘要
我们提出了L1-NORM的二次不受约束的二进制优化（QUBO）公式，这使我们能够对ISING型退火方法（例如量子退火）进行稀疏估计。 QUBO公式是使用Legendre Transformation和Wolfe定理得出的，该定理最近被用于得出relu-Type函数的QUBO公式。结果表明，衍生方法对L1-Norm案例的简单应用导致冗余变量。最后，通过删除冗余变量来获得简化的QUBO公式。
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.
