A second-order cone program has a linear objective and affine constraints taking values in products of second-order cones and nonnegative orthants. Norm epigraphs have the form ; quadratic epigraphs admit the affine lift , equivalent to . Product-cone self-concordant barriers give interior-point methods.
Let , and . The objectivehas the exact second-order cone program liftThe cone ordering here is with , matching second-order cone. The small cone is equivalent to . Hence every lifted feasible objective bounds the original one. Choosing , and proves equality. The sign is necessary for this bounding argument; a negative penalty coefficient would allow increasing to lower the lifted objective without bound.
Using a parameter-two barrier for each Lorentz block and a parameter-one logarithmic barrier for each scalar nonnegative slack gives total barrier parameter . The number of derivative rows is , which need not equal the signal dimension . The fidelity norm remains unsquared and negative derivative values remain unpenalized.
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Second-order cone programming (SOCP) is a type of convex optimization problem that generalizes linear programming and is closely related to quadratic programming.