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Signal estimation problems with smoothness and sparsity priors can be naturally modeled as quadratic optimization with $\ell_0$-"norm" constraints.
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What energy functions can be minimized via graph cuts?
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Adaptive lasso for sparse high-dimensional regression models
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OR forum – an algorithmic approach to linear regression
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Kim, S.-J., Koh, K., Boyd, S., and Gorinevsky, D. (2009) · 2009
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The ALAMO approach to machine learning
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Strong formulations for quadratic optimization with M-matrices and indicator variables
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Structural properties of affine sparsity constraints
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