A SYMMETRIC PRIMAL-DUAL ALGORITHM FOR CONIC OPTIMIZATION BASED ON THE POWER CONE The power cones form a family of convex cones that allow the formulation of a large class of convex problems (including linear, quadratic, entropy, sum-of-norm and geometric optimization) into a unified structured conic format. We introduce a primal-dual interior-point algorithm for the this class of problems, which focuses on preserving the perfect symmetry between the primal and dual sides of the problem (arising from the self-duality of the power cone).