  We discuss the application of random projections to conic programming:
notably linear, second-order and semidefinite programs. We prove general
approximation results on feasibility and optimality using the framework of
formally real Jordan algebras. We then discuss some computational experiments
on randomly generated semidefinite programs in order to illustrate the
practical applicability of our ideas
