From the 1 of 4 linked papers with an AI index.
4 papers
Semismooth Newton methods for degenerate polyhedral projection
Chao Ding, Fuxiaoyue Feng, Xudong Li
The paper develops dual semismooth Newton algorithms for degenerate polyhedral projection problems by exploiting a primal‑dual lifted representation that ensures nonsingular genera…
Stratification for Nonlinear Semidefinite Programming
Chenglong Bao, Chao Ding, Fuxiaoyue Feng +1
This paper introduces a stratification framework for nonlinear semidefinite programming (NLSDP) that reveals and utilizes the geometry behind the nonsmooth KKT system. Based on the…
A Regularized Newton Method for Nonconvex Optimization with Global and Local Complexity Guarantees
Yuhao Zhou, Jintao Xu, Bingrui Li +3
Finding an -stationary point of a nonconvex function with a Lipschitz continuous Hessian is a central problem in optimization. Regularized Newton methods are a classical tool a…
A quadratically convergent semismooth Newton method for nonlinear semidefinite programming without generalized Jacobian regularity
Fuxiaoyue Feng, Chao Ding, Xudong Li
We introduce a quadratically convergent semismooth Newton method for nonlinear semidefinite programming that eliminates the need for the generalized Jacobian regularity, a common y…