# A Newton-CG based barrier method for finding a second-order stationary point of nonconvex conic optimization with complexity guarantees

In this paper we consider finding an approximate second-order stationary point (SOSP) of nonconvex conic optimization that minimizes a twice differentiable function over the intersection of an affine subspace and a convex cone. In particular, we propose a Newton-conjugate gradient (Newton-CG) based barrier method for finding an $(\epsilon,\sqrt{\epsilon})$-SOSP of this problem. Our method is not only implementable, but also achieves an iteration complexity of $O(\epsilon^{-3/2})$, which matches the best known iteration complexity of second-order methods for finding an $(\epsilon,\sqrt{\epsilon})$-SOSP of unconstrained nonconvex optimization. The operation complexity of $O(\epsilon^{-3/2}min{n,\epsilon^{-1/4}})$, measured by the amount of fundamental operations, is also established for our method.

## Citation

arXiv preprint: arXiv:2207.05697