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.OC2026
Block Decomposable Methods for Large-Scale Optimization Problems
Leandro Farias Maia
This dissertation explores block decomposable methods for large-scale optimization problems. It focuses on alternating direction method of multipliers (ADMM) schemes and block coor…
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…