= Interior-point method
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An interior-point method solves constrained <mathematical optimization> problems by maintaining variables in the interiors of their feasible cones or inequality domains. Barrier derivatives are defined there, and damped <Newton methods> keep subsequent iterates in their domains. A <central path> gives a family of barrier-regularized optima whose duality gap approaches zero; a <conic phase-I problem> can supply a strict feasible starting point.
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