3 papers
math.OC2026
A Regularized Hessian-Free Inexact Newton-Type Method with Global Convergence
Leandro Farias Maia, Antonio Victor B. Nascimento, Paulo Sergio M. Santos +1
We propose a regularized Hessian-free Newton-type method for minimizing smooth convex functions with Lipschitz continuous Hessians. The algorithm constructs an approximate Hessian…
math.OC2024
An Adaptive Proximal ADMM for Nonconvex Linearly Constrained Composite Programs
Leandro Farias Maia, David H. Gutman, Renato D. C. Monteiro +1
This paper develops an adaptive proximal alternating direction method of multipliers (ADMM) for solving linearly constrained, composite optimization problems under the assumption t…
math.OC2024
An Adaptive Cubic Regularization quasi-Newton Method on Riemannian Manifolds
Mauricio S. Louzeiro, Gilson N. Silva, Jinyun Yuan +1
A quasi-Newton method with cubic regularization is designed for solving Riemannian unconstrained nonconvex optimization problems. The proposed algorithm is fully adaptive with at m…