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quant-ph2020★ 2 cited
Derivation of QUBO formulations for sparse estimation
Tomohiro Yokota, Makiko Konoshima, Hirotaka Tamura +1
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 qu…
quant-ph2018★ 7 cited
Quadratic unconstrained binary optimization formulation for rectified-linear-unit-type functions
Go Sato, Makiko Konoshima, Takuya Ohwa +2
We propose a quadratic unconstrained binary optimization (QUBO) formulation of rectified linear unit (ReLU) type functions. Different from the q-loss function proposed by Denchev e…