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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.18858 |
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Table of Contents:
- In this work we develop and analyze a semi-smooth Newton method for the general nonlinear conic programming problem. In particular, we study the problem with a generalized simplicial cone, i.e., the image of a symmetric cone under a linear mapping. We generalize Robinson's normal equations to a conic setting, yielding what we call the conic projection equations. The resulting system is equivalent to the KKT conditions associated with the nonlinear conic programming problem. A semi-smooth Newton iteration is proposed for solving it, and local quadratic convergence is established. We study properties of generalized simplicial cones and prove strong semi-smoothness of the projection operator onto them. Numerical experiments compare the method against a recent smoothing Newton approach on the circular cone programming problem, and we also apply it to the low-rank matrix completion problem.