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Author

Ru-Yu Liu

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Preprint Sep 2026

A proximal-linearized NEP method for composite optimization with conic and manifold constraints

iPLNEP is shown to achieve an $O(\epsilon^{-2})$ worst-case iteration complexity bound for finding an $\epsilon$-stationary point, and provides the first proximal-linearized NEP framework with provable oracle complexity guarantees for DC composite optimization with conic and manifold constraints.

Hao He, Ru-Yu Liu, Shao-Hua Pan · 0 citations
Preprint Sep 2026

A proximal linearized NEP method for composite optimization with conic and manifold constraints

This paper studies DC composite optimization problems with simultaneous conic and manifold constraints. We propose an inexact proximal linearized exact penalty algorithm based on a distance-based penalty function for the conic constraint. The algorithm successively computes approximate minimizers of proximal linearizat...

Hao He, Ru-Yu Liu, Shao-Hua Pan · 0 citations

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