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Adiabatic Quantum Feature Selection for Sparse Linear Regression
This paper aims to address the intractability of sparse linear regression with $\ell_0$ norm using adiabatic quantum computing, a quantum computing paradigm that is particularly useful for solving optimization problems faster.
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