Quadratic program

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(QP). Classically, this is to optimize a quadratic function over a polyhedron, defined by linear equations and/or inequalities:

\max \left \{\frac{x^T Qx}{2} + cx: Ax \le b\right \},

where LaTeX: Q is symmetric (without loss in generality). A QP is convex if its quadratic form matrix LaTeX: (Q) is positive semi-definite. More generally, there could be quadratic constraint functions.

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