DERIVING DUALITY FOR L_P-NORM OPTIMIZATION USING CONIC OPTIMIZATION In this talk, we formulate the l_p-norm optimization problem as a conic optimization problem and derive its standard duality properties. We first define an ad hoc closed convex cone and derive its dual. We express then the standard l_p-norm optimization primal problem as a conic problem involving this cone. Using conic duality, we derive the dual of this problem and prove the well-known regularity properties of this primal-dual pair, i.e. zero duality gap and dual attainment.