  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.
